What shipped, when

Blog — As of June 18, 2026, Gemini CLI and the Gemini Code Assist IDE extensions stop serving requests for Google AI Pro, Ultra, and free-tier users; Standard/Enterprise licenses and paid API keys are unaffected. The post breaks down exactly who's affected, what keeps working, and what Antigravity CLI carries over (Agent Skills, Hooks, Subagents, Extensions — without 1:1 parity).

Blog — SpaceX agreed to buy Cursor (Anysphere) for $60B in SpaceX stock, four days after the company's IPO. The post covers the deal terms, why SpaceX needed Cursor to replace the failed xAI, and what it means for builders using Cursor today.

Prompt library — Added 7 prompts across four categories: a structured research paper summary and cross-study comparison (research + analysis), a newsletter issue builder and landing page copy generator (writing), and two investor update templates — one for monthly updates, one for the "we missed the numbers" email (writing). All adapted from production prompt packs.

Best AI picks by role — Added 9 more "Best AI for X" surfaces: designers, HR teams, product managers, content creators, meeting notes, agencies, consultants, e-commerce operators, and researchers. Three fact-checked picks per role with explicit caveats on when each tool earns its cost.

Best AI picks by role — Added 7 new "Best AI for X" surfaces: sales reps, marketing managers, founders, engineers, customer support, cold email outreach, and image generation. Three opinionated picks per role, with specific reasoning on when each tool earns its cost.

Stop prompting. Start observing. — Before AI can replace any part of your week, you have to see it clearly. The one-week audit, the four-bucket sort, and the trap of automating work that shouldn't exist at all.

Title and meta descriptions on two /learn/ship-own-stack migration guides updated to better match search intent (position 4–7, 0% CTR → cleaner action-first copy).

Old prompt-craft URLs were indexed by Google but returning 404. Added 301 redirects to the new /learn/prompt-engineering/foundations paths.

Prompt Engineering is now a first-class category in /learn, alongside Working with AI, Building & Shipping, and Stacks & Systems.

Three pillars, twelve guides (four existing, four new, four coming soon):

Prompt fundamentals — the four foundations: what makes a prompt work, XML structure and roles, few-shot examples, and five patterns that work in any model.

Prompting techniques — four new guides: chain-of-thought prompting, prompt chaining, role prompting, structured output control.

Building with prompts — system prompts, iteration method, injection defense, cross-model porting — coming soon.

MCP in plain English — and what to install first — what the protocol is, what it isn't, the three primitives, and which three servers to install first.

Title and meta descriptions updated on three /learn/ship-own-stack pages to match GSC query intent.

How to write AGENTS.md so AI doesn't break your repo — seven sections in impact order, a Claude-draft workflow, and a 7-point checklist.

Workflows just got a new shape: outcome bundles — cross-role journeys priced at $12.49, sitting alongside the $19 role packs. Each is a spine plus five new deep workflows that get one outcome done end to end:

• Build, Ship & Host Your Own Product — idea → a hosted, paid product: auth + Stripe, CI/CD, monitoring, domain + email, cost control.
• Launch Your Product (GTM) — positioning, launch week, SEO foundation, measurement, and first customers, across the marketing, sales and founder packs.
• Ship an AI Feature on Claude — API integration, cost + quality tuning, RAG, observability, and pre-ship verification.

The bundles tie into three new free skills — hosting-stack-selector, auth-and-payments-setup, production-monitoring-setup. And workflow pages now show the skills and prompts each one references as clickable links, so the library is wired together instead of siloed.

Twenty-six new skills landed on /skills, bringing the library to 200. The biggest additions are on the developer side: a Claude API Builder (prompt caching + streaming by default), a Browser Automation Driver for end-to-end UI checks, React performance and composition reviewers, a Postgres performance reviewer, and test-driven-development. Marketers get a Voice-of-Customer researcher, a Marketing Psychology advisor, and SEO additions for site architecture and structured data. Each one is a self-contained SKILL.md you can install, written for utility rather than a tool dump — and de-duplicated against everything already in the library.

How to write AGENTS.md so AI doesn't break your repo — the standing instruction file every AI-built project needs and most skip. What to put in it (seven sections in order of impact), what the cost of skipping each section is, and a step-by-step workflow for having Claude draft one without ending up with 400 lines of generic filler. Closes with a 7-point checklist for the final file. Links out to /glossary/cursorrules and the working-with-existing-code guide.

Added a six-question FAQ section to How to migrate a Base44 app covering the questions that don't fit cleanly into the path walkthroughs: Builder plan gating, data export behavior, how to scope the SDK surface area before starting, hosting alternatives to Vercel, and whether the migration is reversible. The guide title also sharpened to surface "Vercel, eject, Supabase" — the three destination options — which is what search intent actually shows up as.

Filling a real gap in /learn/ai/ship-own-stack: how to migrate a project off the AI builder it was prototyped in. Each guide is written against the builder's own documentation, with the host-side migration paths covered end to end.

Four new guides:

• Migrate from Lovable — GitHub sync, Vite on Vercel, deciding whether to keep the Lovable-provisioned Supabase or move to your own, fixing auth redirect URLs, replacing Edge Functions.
• Migrate from Replit — following Railway's official Replit migration guide. Downloading the zip, removing .replit and replit.nix, translating the run command, migrating Postgres with pg_dump, replacing Replit Auth.
• Migrate from Emergent — splitting the FastAPI + React + MongoDB stack across Vercel (frontend), Railway/Render/Fly (backend) and MongoDB Atlas (data). mongodump/mongorestore, CORS, AI provider key rotation.
• Migrate from Base44 — three depths: move only the frontend (recommended starting point), eject to a new Base44 backend you own, or fully rebuild against Supabase + Postgres. Why partial migration is usually the right first move.

Hub guide rewritten: graduate-from-nocode is now broader than the original Lovable/Bolt scope, with the five graduation signals refined and explicit links into the per-builder pages. It also covers what graduating does not fix — speed, security, or operational time — which is the part most articles skip.

Why now: "migrate from X" queries for Lovable, Replit and Emergent have rising volume across SEO surfaces, none of the existing answers cover all four major builders with verified source citations, and the pillar already had the deploy-walkthrough that these guides hand off into.

/prompts — 65 new prompts across 10 categories (112 → 177 total):

• Code (+14): agent steering before edits, course-correct mid-task, incident investigation across logs and deploys, IaC plan translation, plain-English log queries, TDD with AI, codebase archaeology prompts
• Sales (+12): QBR talking points, strategic account plans, renewal pitch, battlecards, territory planning, exec pipeline updates
• Productivity (+10): quarterly OKRs with non-goals, hiring roadmaps, 1:1 templates, cross-team conflict mediation, exec briefings
• Analysis (+10): funnel drop-off with ranked hypotheses, customer health rubrics, A/B test interpretation, attrition detection, forecasts with confidence intervals
• Research (+9): competitor pricing benchmarks, regulatory landscape, compensation benchmarks, industry trends with evidence vs. narrative separated
• Writing (+8): PRD drafts with acceptance criteria, town hall talking points, reorg comms, vision statements
• Design (+2): customer journey maps, positioning matrices

/skills — 43 new skills across 8 packs (132 → 175 total):

• Developer (+11): CI/CD architect, MCP server builder, RAG architect, LLM cost + quality tuner, observability designer, SLO designer, dependency auditor, feature flags architect
• Founder (+11): CFO advisor, Chief AI Officer advisor, plan stress-tester, pre-mortem generator, adversarial board prep, first-customer interview loop
• Marketer (+10): cold email sequence, paid ads architect, A/B test coach, brand voice extractor, landing-page CRO audit, pricing page optimizer
• Sales-rep (+8): RFP responder, champion coaching plan, pricing conversation coach, multi-thread account
• Customer-success (+3): onboarding playbook builder, health score rubric designer, expansion play architect

End-of-May surface refresh covering the editorial layer on top of all the content shipped this week.

Three new spotlights on /spotlights:

• LLM Cost + Quality Tuner (skill) — the structured exercise for cutting LLM bills 30–70% without breaking outputs. Profiling first, then 7 ranked levers with quality risk per lever.
• OpusClip (tool-drop) — the long-video to short-clip pipeline that stopped being a hack. Active-speaker reframing that holds up, viral-score ranking that does the picking-work for you.
• May 2026 stack — understand before you build (monthly-stack) — the editorial thesis behind this month's shippings. Why we built Foundations + Paths + indie-tool-evaluation as a set, what we deliberately skipped (gamification, AppSumo dump, new pages), what is next.

/best — end-of-month review. All four surfaces (coding stack, research tools, free AI setup, prompts for writing) reviewed against the month's new releases and changes. Picks held in every case. Each surface has a new past[] entry documenting what was considered for inclusion and why the current ranking still wins.

Two complementary shippings to address the long tail of AI tools — both the mainstream gaps and the question of how to evaluate the indie tools that don't appear in mainstream listicles.

/tools — 8 additions filling category gaps:

• Productivity: Grammarly (writing assistant across every app), Sudowrite (AI for fiction and screenwriting), Superhuman (premium email with AI drafting)
• Video: OpusClip — long-form to short-clip pipeline with viral-score predictions
• Voice: PlayHT — 900+ voices across 140+ languages, multilingual TTS at scale
• Sales/Marketing: Vista Social (social media management), AdCreative.ai (AI-native ad creative with conversion predictions), Textio (hiring and performance language)

Brought /tools from 198 to 206 entries across the catalog.

New guide: Evaluating an indie AI tool before you commit — a 15-minute pre-commit checklist for any AI tool you're considering paying for. Covers wrapper-risk, team and funding signals, the changelog test, community signal, the "try your worst case" test, lock-in audit, and the LTD-specific risks (acquisition risk, feature gating, support cliff). Plus an honest read on when indie beats incumbent and when it doesn't.

Source: curated from ClickUp, Lindy, Lovable, and Alai's 2026 "best AI tools" lists; cross-checked against AINews's existing 198-tool catalog to find genuine gaps. AppSumo deals were considered but parked for a future /deals batch (documented in roadmap).

Two follow-ups to the /learn/paths feature.

Two new paths.

• Founder → AI-augmented operator — 9 guides, ~95 min. Foundation + customer-interview habit + architecture decisions + the solo-founder applied chapter.
• Designer → AI-assisted workflows — 7 guides, ~55 min. Prompt craft heavy (designers benefit disproportionately from few-shot), the designer playbook, and a bridge to building working prototypes.

Total: 5 paths now.

"You are on a path" indicator. When you open any guide that sits inside one or more paths, a small banner near the top tells you which path(s) the guide belongs to and the step position ("step 3 of 8"). One click takes you back to the path overview. Server-rendered, no JS cost.

Two related shippings in /learn — the technical-depth pillar and the multi-guide path feature that ties everything together.

New pillar: "How AI works" (foundations) — 8 substantial guides for the operator who wants to understand the mechanism, not just use it:

• How large language models work — the mental model that fixes most "why did AI do that" moments
• What is a token in AI? — the unit that controls cost and output
• Context windows explained — what they limit, what they do not, lost-in-the-middle effect
• Embeddings explained — how AI represents meaning as numbers
• Transformers and attention — the architecture under every modern model
• Fine-tuning vs RAG vs prompting — which one fits your problem
• How AI agents work (and where they break) — the mechanism + six predictable failure modes
• How to evaluate an LLM feature is working — without fooling yourself

New feature: Learning paths — three sequenced multi-guide routes through the library, shaped by role:

• Zero → AI-augmented operator — 8 guides, ~4 weeks at 15 min/week
• Engineer → AI-coding fluency — 9 guides, ~6 weeks at 15 min/week
• PM → AI-aware product thinking — 7 guides, ~3 weeks at 25 min/week

Source pattern: foundations distilled from Microsoft AI-For-Beginners and the broader academic curriculum; learning paths borrowed from DataCamp's role-based "how to learn AI" structure. Both adapted to AINews voice — utility-framed, model-agnostic, no buzzwords.

New guide in /learn/ai/get-started: Free AI courses worth your time (from the people who built it).

Opinionated short list — Anthropic Academy, OpenAI Academy, Google ML Crash Course + Analytics Academy, Hugging Face NLP Course, Elements of AI (University of Helsinki), Google Cloud Skills Boost.

For each: what it's good for, who it's for, and what to skip. With a suggested starting order by role at the end.

Also explicitly named what we left off and why (random YouTube playlists, "30 day boot camp" funnels, "100 prompts that change your life" lists). Filtering matters — the value isn't a longer list, it's a shorter one you can trust.

New pillar in /learn/ai: Prompt craft. The patterns that hold across every model — not "10 magic words" content, the actual fundamentals.

Three guides, model-agnostic, ship today:

• What makes a prompt actually work — the "brilliant but new employee" mental model, the colleague test, and the five patterns that move quality every time (specific format, why-not-just-what, examples, role assignment, constraints up front).
• Structuring prompts with XML, roles, and sections — when to start structuring (~200 words), why <tags> beat prose for long prompts, the role-1-sentence quality upgrade, and the hierarchy that matters at 20k+ tokens (instruction at the END).
• Few-shot examples: when they help, how to write them — the single highest-leverage technique. The 3 rules (relevant, diverse, structured), the 3–5 sweet spot, why one bad example corrupts the whole output, and the meta-trick of asking the model to critique your examples.

Source pattern: distilled from Anthropic's official prompt-engineering reference, generalized to be model-neutral. AINews voice — no "magic words," no "10x your AI productivity," utility over inspiration.

Eighteen substantial new skills added to the four highest-engagement role packs. Each one is a self-contained installable skill — methodology + workflow + anti-patterns + tone notes. Source material curated from the broader Claude Code agent-skills ecosystem (MIT-licensed), then rewritten for AINews voice (utility framing, no Claude-Code-specific commands, no enterprise-skill-tier theatrics).

By pack:

• /skills/founder (12 → 17): Plan Stress-Tester, Pre-Mortem Generator, Hard Call Framework, Adversarial Board Prep, First-Customer Interview Loop.
• /skills/sales-rep (15 → 20): RFP / Security-Questionnaire Responder, Deal-Desk Discount Justifier, Champion Coaching Plan, Multi-Thread the Account.
• /skills/developer (16 → 20): Codebase Onboarding Doc Builder, SLO + Error Budget Designer, LLM Cost + Quality Tuner, Dependency + CVE Auditor.
• /skills/marketer (13 → 17): Technical SEO Audit, Answer-Engine Optimization Brief, Landing-Page Conversion Audit, Referral Program Designer.

Brought /skills from 132 to 150 skills across 12 role packs.

Companion batch to today's code-prompt drop. 26 additions across six categories — strategic work that's usually buried in role-specific playbooks, generalized into AINews voice.

By category:

• /prompts/sales (10 → 16): strategic account plans, battlecards with "where they win" honesty, renewal pitches grounded in real outcome numbers, territory planning, exec pipeline updates, public-domain proof-point research.
• /prompts/productivity (11 → 16): quarterly OKRs with explicit non-goals, hiring roadmaps with the rationale baked in, 1:1 templates that surface what skip-levels miss, cross-team conflict mediation, exec briefings under 4 minutes.
• /prompts/writing (10 → 14): PRD drafts with observable acceptance criteria, town hall talking points, reorg comms sequenced by audience over 24–72h, vision statements that aren't corporate posters.
• /prompts/research (10 → 14): competitor pricing benchmarks (public-source only), regulatory landscape by region, compensation benchmarks with assumptions visible, 3-year industry trends with evidence vs. narrative separated.
• /prompts/design (10 → 12): customer journey maps with friction marked honestly, 2x2 positioning matrices that pressure-test self-flattering axes.
• /prompts/analysis (11 → 16): funnel drop-off with 3 ranked hypotheses, customer health rubrics that discriminate (not wallpaper), A/B test interpretation including confounders most readouts skip, attrition pattern detection, forecasts with confidence intervals.

Source pattern: generalized from OpenAI Academy's role-based prompt packs, rewritten to AINews multi-section voice — no "ChatGPT for X" framings, no "leverage / robust / seamless," utility over inspiration.

Fourteen additions to /prompts/code, targeting the gaps the existing 20 prompts didn't cover well: planning before agents touch code, steering them mid-task, and translating production signals into next moves.

Highlights:

• Plan a multi-file change before any edits — file list + risks + out-of-scope, before the agent writes a single line. Stops "rewrote half the project" outcomes.
• Course-correct without rewinding + Narrow a change that went too broad — the steering moves you need when the direction is right but the execution drifted.
• Investigate a production incident across logs, deploys, and config — ranked causes, each with the signal that confirms it. Not a single guess.
• Translate IaC plan output to plain English — Terraform / Pulumi / CDK plans → what's created, replaced, destroyed, what's dangerous. With an apply/don't-apply verdict.
• Query logs in plain English (and see the query) — ask, see the SQL/KQL, approve, run, interpret. With a scan-size guardrail.
• Drive implementation from tests (TDD with AI) — strict order: tests fail → approve → implement → green. Never weaken the test.
• Get oriented in a new codebase, Trace why code looks the way it does, Trace what happens when a user does X — the three onboarding / archaeology prompts you reach for in week one of a new repo.
• Map the edge cases the happy path is hiding — 8 categories of what-can-go-wrong with explicit "not covered" flagging.
• Plus: anchor to existing patterns, close coverage gaps without gaming the metric, diagnose from cloud-console screenshots.

Brought /prompts/code from 20 to 34 prompts.

Four new beginner-intent guides under /learn/ai/productivity-playbooks. Each one answers a specific work-intent query with a working model, concrete examples, and a clear "where it goes wrong" section — not generic tips:

• How to use AI for research — orient, find gaps, pressure-test, turn into output. With the verification step.
• How to write better emails with AI — 5-input model, revision-mode, ban-list, when not to use AI for email at all.
• How to use AI for meetings, notes, and follow-ups — decision extraction, action items with owners, same-hour follow-up.
• How to use AI for spreadsheets and analysis — formula generation, anomaly spotting, code-interpreter mode, and the math you can never trust AI to do alone.

Pillar renamed in nav from "Productivity playbooks" to "Use AI for work" — same URL, clearer entry point.

Several visual and SEO fixes shipped together:

• New favicon + logo matching the gradient-A brand. Header, footer, and all browser tabs share one identity now.
• Dark-mode contrast bug in all /learn guide pages fixed (prose prose-invert was always-inverted with conflicting overrides — body text was unreadable on dark backgrounds).
• Aurora background now edge-to-edge in both light and dark mode (the local hero gradient was being clipped inside the max-w-7xl container).
• 404 cleanup: /favicon.svg + /apple-touch-icon variants now resolve, eliminating ~830 404s/week (12% of all 404 traffic).
• Glossary page titles retargeted from "X — what it means in plain English" to "What is X?" for cleaner query match.
• Redirect for /imgs/logox.png (external link rot) → current brand icon.

Two-part RAG update driven by SEO data showing rising impressions on "rag", "rag meaning llm", "what is rag" queries hitting the glossary page.

• /glossary/rag — rewritten for definition-intent. Same content, sharper structure: explicit "RAG vs fine-tuning", "RAG vs long context", "RAG vs plain search" sections. Skimmable.
• NEW: How RAG works, and when to use it — the explainer version. Each pipeline step in detail (chunking, embedding, retrieval, hybrid search, reranking, generation), when to use RAG, when not to, 10 common beginner mistakes, and a minimal modern stack.

Glossary = definition. Guide = teaching. Different jobs, cross-linked.

/learn is now structured as a beginner-first hub with three curated paths (New to AI / Use AI at work / Build with AI). Four new cornerstone guides land today:

• Getting started with AI: a 30-minute starter path — the hub guide that links to every other beginner read.
• What AI is good at, and what it still gets wrong — the capability map for new users.
• How to verify AI output before you trust it — opens the new "Verify and trust" pillar.
• Prompts vs Skills vs Workflows vs Agents — when to use which — the decision framework for picking the right AI format for the job.

Also retitled pick-your-daily-ai to "Which AI should I use? Claude vs ChatGPT vs Gemini" to better match how people actually search.

New guide at /learn/ai/use-cases-by-role/best-ai-prompts-for-sales-reps: eight sales prompts that survive contact with real buyers — cold email, discovery openers, objection handling, follow-up sequences, account research, win-back, internal champion enablement, LinkedIn DMs. Each one with the ban-list that keeps the output from sounding generic. Companion piece to the sales prompt library and the Sales pack.

Workflows section is live — 164 templates across 5 packs, 40 free.

• Packs — dev, founder, HR, marketing, sales
• Bundles — per-pack or all-access
• What you get — Claude Code commands, agent runbooks, step-by-step playbooks scoped to a role

New post at /blog/how-to-review-an-ai-pr: a 12-point review checklist for AI-generated PRs — description-vs-diff alignment, import resolution, error handlers, async boundaries, schema drift, injection holes, config permissiveness, and rollback plans — plus how to scope the review so it gets done. Companion piece to AI tests aren't testing anything.

New hub at /mcp: a curated catalog of 31 Model Context Protocol servers across 7 categories — file & code, database, browser & web, productivity, data & analysis, dev-ops, and utility.

• What it is — the 60-second explanation of MCP for people who haven't read the spec, plus a quick rundown of which AI clients support it today (Claude Desktop, Claude Code, Cursor, Zed, Windsurf, Cline).
• 31 hand-picked servers including Anthropic reference (filesystem, git, memory, fetch, time, sequential-thinking), commercial (GitHub, Linear, Notion, Stripe, Sentry, Cloudflare, Vercel, Supabase, MongoDB), and infrastructure (AWS, Docker, Playwright, Firecrawl, Tavily).
• Install snippets — copy-paste claude_desktop_config.json config for the seven reference servers; repo + docs links for the rest.
• Integrated into /search as a new section, and cross-linked from /agents and /glossary/mcp.

Catalog expanded from 179 to 197 tools, with three new categories that were missing for the 2026 landscape:

• Local & on-device AI (6 tools) — Ollama, LM Studio, llama.cpp, Jan, MLX, GPT4All. For running open-weight models without sending tokens to a cloud.
• Evals & observability (6 tools) — Braintrust, Helicone, Langfuse, Arize Phoenix, Patronus AI, LangSmith. The "did my LLM change actually help?" category.
• Sandboxes & code execution (4 tools) — E2B, Vercel Sandbox, Modal, Daytona. Isolated environments for running AI-generated code safely.

Plus two filling existing-category gaps: Vercel (deployment platform — ironically absent until now) and Zed (AI-native code editor).

Seven new prompts in /prompts/code, all targeting AI-builder workflows where verification is the bottleneck:

• Design a verification gate for an AI agent step — treat agent output as hypothesis, define what's checked before it's trusted downstream.
• Review AI-generated output as a hypothesis — sort verified vs assumed vs possibly fabricated, ranked checks to run before accepting.
• Audit a spec for hidden assumptions — find the gaps before an agent or junior engineer fills them with guesses.
• Scope a new build phase with testable acceptance criteria — phase-gated, with explicit exit conditions.
• Generate a debugging hypothesis tree — ranked by likelihood × cheapness-to-verify, not by what's most interesting.
• Design a Postgres data model for a feature — schema, constraints, indexes, denormalization decisions with reasons.
• Write a technical decision record (ADR) — for future-you, six months from now, having forgotten everything.

The /code prompt count is now 20 (was 13).

New post at /blog/pre-deploy-checklist: a 24-point checklist across eight categories (secrets & auth, database, AI costs, frontend, error handling, rate limits, observability, rollback) for AI builders who get 90% of the right decisions and 10% of the catastrophically wrong ones. Includes a copy-paste version.

Major discoverability pass so AINews shows up in Google AI Overviews, ChatGPT citations, and Perplexity:

• New /llms.txt — structured site index for AI crawlers (700+ lines covering every hub, blog post, comparison, glossary term, tool, skill, prompt category, role page, guide, and recent news article). Generated from the same data sources as /sitemap.xml.
• JSON-LD structured data — Organization + WebSite + SearchAction schemas on the homepage; BlogPosting + BreadcrumbList on every blog post. Sitelinks searchbox now eligible.
• Per-post OG images — every blog post now gets a unique 1200×630 image with its title as hero, auto-generated at /blog/[slug]/opengraph-image. Used in social sharing, Twitter cards, LinkedIn unfurl, Slack previews, and BlogPosting JSON-LD.
• Default openGraph.images on layout so every page has a fallback social preview.

Post-promotion sends now lead with the post as hero (with its per-post OG image), not buried under changelog cards. Changes:

• Hero image on top is post-specific (no longer the generic site OG)
• Subject line is the post title (no "AINews · X updates" prefix when promoting a post)
• Larger H1 (30px, weight 800) and CTA button (14×26 padding, 15px font) — matches the site's hero proportions
• Changelog moved to a compact "Also this week" list at the bottom
• Dropped meaningless FEATURE/CONTENT tag pills that appeared on every card
• Digest-only mode (no post) keeps the existing card layout

New post at /blog/vibecoding-what-to-think-about: the five things that actually break when non-engineers ship AI-built apps — API keys in the frontend, fake auth, prompt-deletable databases, uncapped costs, and the "works for me" trap — with a fix for each.

Four changes shipped together:

• New section at /open — opinionated explainer of open-source AI. What "open weights" actually means, the models that matter in May 2026 (DeepSeek V4, Llama 4, Qwen 3.5/3.6, Kimi K2.6, gpt-oss), where to run them, and the open tools built on top. Decision matrix for open vs frontier plus the licensing pitfalls people miss.

• OpenClaw added to the tools catalog — Peter Steinberger's autonomous local AI agent, the fastest-growing open-source project on GitHub. MIT-licensed; runs locally; acts via WhatsApp / Telegram / Discord / Signal with persistent memory.

• "Blog" renamed to "Posts" in nav, footer, and section headers. The content type stays identical (weekly long-form notes); the label was journal-flavored, the actual posts are practical playbooks. URL /blog/[slug] unchanged.

• 17 new sources in /news — Anthropic, Anthropic Engineering, Claude Code Changelog, Google AI, Meta AI, xAI, Mistral, Cohere, Thinking Machines, The Batch, Perplexity, Together AI, Groq, Ollama, Vercel, Windsurf, Simon Willison. Up from 20 to 37 feeds total.

Companion to yesterday's post on hallucinations, loops, and confident-wrongness. New skills you can install:

• AI Output Verifier — audits AI-generated code for hallucinated APIs and silent rewrites
• Loop Breaker — diagnoses why an agent is stuck and produces a clean restart prompt
• Context Grounding Brief — builds the context bundle that prevents hallucinations before they happen
• AI Feature Pre-Ship Checklist — verification checklist for AI-built features before they touch real users

New prompts in /prompts/code (verify AI code, escape an agent loop, ground context before coding), /prompts/productivity (set a time budget for AI tasks), and /prompts/analysis (sanity-check AI output before acting on it).

New post at /blog/your-ai-is-confidently-wrong: the four failure modes that actually empty your AI budget — hallucinations, loops, over-broad rewrites, and long-session degradation — with concrete fixes for each.

Major expansion of /coding:

• Mode picker — pick "Just starting / Solo / Production / Team lead" and get the rest of the page through that lens.
• Recommended starter stacks for each mode (concrete picks, not vague advice).
• Repo file templates — copy-paste AGENTS.md, CLAUDE.md, .cursorrules, PLAN.md, IMPLEMENTATION.md, REVIEW.md.
• Verification matrix — when each level (automated / model review / independent verifier / human) is required.
• Escalation rules for risky changes (auth, payments, destructive migrations).
• Good-vs-bad examples for repo instruction files.

Plus 9 new AI builders in /tools: Codeium, Cody by Sourcegraph, Emergent, Base44 (Wix), Natively, Supermaven, StackBlitz, JetBrains AI Assistant, Amazon Q Developer.

Full pre-launch security audit and patch round. Closed:

• Stored XSS vector in JSON-LD (escaped </script> and U+2028/2029 properly).
• DB credential footgun in Next config.
• Missing rate limits on LLM endpoints (per-IP + body fingerprint).
• Newsletter mailbomb risk (rate limit + honeypot + per-recipient cooldown).
• Missing security headers (CSP, HSTS, frame, referrer, nosniff, permissions).
• Removed two obsolete privileged setup routes.

Site is now safe to deploy publicly.

First public version of AINews. Hand-curated AI reference site for builders:

• 128 Claude Skills across 12 packs (developer, founder, marketer, sales, HR, customer success + capability packs for slides, sheets, docs, PDFs, web/UI, diagrams).
• 100 prompts organized by job-to-be-done.
• 178 AI tools with comparisons.
• /learn guides on validation, distribution, pricing, integration, automation.
• /glossary of 80+ AI terms in plain language.
• /for/[role] role-specific stack recommendations.

All free, no signup, MIT-licensed code, CC BY-NC content.