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Hacker News - Newest: "AI"

AI can't read an investor deck AI as an attorney? Student uses ChatGPT, Gemini to sue UW over alleged racial discrimination Hacking MCP Servers in AI Systems – The Rug Pull: Tool Changes After Approval GitHub - MeepCastana/KubeezCut: Free Web based video editor GitHub - GenAI-Gurus/awesome-eu-ai-act: Curated tools, official sources, OSS, templates, and guides for EU AI Act compliance. Can AI judge journalism? A Thiel-backed startup says yes, even if it risks chilling whistleblowers Coming soon: 10 Things That Matter in AI Right Now DARPA built an AI to fact-check enemy weapons claims What explains heterogeneity in AI adoption? When AI Meets Muscle: Context-Aware Electrical Stimulation Promises a New Way to Guide Human Movements - Department of Computer Science AI Changed How We Build. It Did Not Change What Matters. Linux rules on using AI-generated code - Copilot is OK, but humans must take 'full responsibility for the… Meta spins up AI version of Mark Zuckerberg to engage with employees Code Mode: Let Your AI Write Programs, Not Just Call Tools | TanStack Blog GitHub - Delavalom/graft: Go framework for building AI agents. Type-safe tools, multi-provider (OpenAI, Anthropic, Gemini, Bedrock), zero vendor SDKs. India's TCS tops estimates, says new AI models did not dent services demand Gen Z's fading AI hype Strong feeling: we are in a folded AI reality GitHub - machinarii/total-recall-catalog: A reference catalog of latest knowledge retrieval, memory & RAG systems GitHub - mensfeld/code-on-incus: Give each AI agent its own isolated machine with root, Docker, and systemd. Active defense detects and stops threats automatically.. Quantization, LoRA, and the 8% Problem: Benchmarking Local LLMs for Production AI Iran war: We spoke to the man making Lego-style AI videos that experts say are powerful propaganda Powell, Bessent discussed Anthropic's Mythos AI cyber threat with major U.S. banks GitHub - immartian/bellamem: Persistent belief-graph memory for AI agents. Retrieves decisive context by importance — not recency, not RAG, not /compact. recursive-mode: The Repo-Native Operating System for AI Engineering After the attack on Sam Altman's home, will AI CEO's go on the offensive? The biggest advance in AI since the LLM Opus 4.6 vs GPT 5.4 One Prompt Unity World Generation Test “AI polls” are fake polls Client Challenge Can AI be a 'child of God'? Inside Anthropic's meeting with Christian leaders How to Switch AI Chatbots and Why You Might Want To GitHub - MattMessinger1/agentic_refund_guardrail: Safe refund policy layer for AI agents — Python + TypeScript. Same behavior, shared tests. Adam/papers/emergent_values_whitepaper.md at master · strangeadvancedmarketing/Adam Ask HN: How do you stop playing 20 questions with your AI coding tools How far can automation and AI support psychotherapy? - @theU GitHub - stagas/rtdiff: realtime git diff gui and AI-assisted commits A Mac Studio for Local AI — 6 Months Later A History of the Early Years of AI at the University of Edinburgh Why AI Coding Tools Still Feel Stuck on Localhost MSN AI Datacenters Are Becoming Strategic Targets twitter.com Penn Researchers Use AI to Surface Unreported GLP-1 Side Effects in Reddit Posts Show HN: MoodSense AI (ML and FastAPI and Gradio, Deployed on Hugging Face) Moodsense Ai - a Hugging Face Space by aman179102 AI models are terrible at betting on soccer—especially xAI Grok GitHub - xialeistudio/echoic GitHub - HimashaHerath/github-dev-wrapped: AI-powered weekly GitHub activity reports deployed to GitHub Pages GitHub - alejandrobalderas/claude-code-from-source: Architecture, patterns & internals of Anthropic's AI coding agent — reverse-engineered from source maps AI and Tech brief: Ireland ascendant GitHub - Titovilal/context0: Context0 - Never Surrender Training for a Marathon with an AI Coach: What Worked and What Didn't Cyber Pulse: Agentic Intel - Apps on Google Play I Built an AI PR Reviewer That Catches Bugs by Not Looking for Bugs Gen Z workers are so fearful AI will take their job they’re intentionally sabotaging their company’s AI rollout | Fortune How AI Is Reimagining the Game of Golf–For Both Players and Courses GitHub - nattergabriel/reseed: A CLI tool for managing and distributing agent skills across projects Is SVG the final frontier? 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MSN GitHub - visionscaper/collabmem: Enabling long-term collaboration with Agentic AI - building up episodic and world model memory over time with in-context awareness We gave an AI a 3 year retail lease in SF and asked it to make a profit | Andon Labs AI Code is Hollowing Out Open Source, and Maintainers are Looking the Other Way What leaked "SteamGPT" files could mean for the PC gaming platform's use of AI AI is the boss at this retail store. What could go wrong? GitHub - Wuzu11517/agentic-proxy: Local proxy meant to help reduce With Drones, Geophysics and ArtificiaI Intelligence, Researchers Prepare to Do Battle Against Land Mines A Single Operator, Two AI Platforms, Nine Government Agencies: The Full Technical Report 在 Steam 上购买 FriedrichAI: Offline AI 立省 10% GitHub - inevolin/resume-cli: Hit Claude usage limits? Resume any AI coding session elsewhere. Switch tools at zero friction. GitHub - atripati/ark: AI Runtime Kernel — a context operating system for AI agents. Eliminates tool bloat, loads only what’s needed, and gives LLMs their reasoning space back. How to Build a Secure AI PR Reviewer with Claude, GitHub Actions, and JavaScript This Startup Wants You to Pay Up to Talk With AI Versions of Human Experts Intel Arc Pro B70 Brings 32GB VRAM to Local AI for $949 WordPress 7.0: The Good, the AI, and the Still Missing AI on the couch: Anthropic gives Claude 20 hours of psychiatry IatroBench: Pre-Registered Evidence of Iatrogenic Harm from AI Safety Measures AI Agents Know About Supabase. They Don't Always Use It Right. The history and future of AI at Google, with Sundar Pichai Inside an AI‑enabled device code phishing campaign How Meta Used AI to Map Tribal Knowledge in Large-Scale Data Pipelines AI for Systems: Using LLMs to Optimize Database Query Execution Forecasting the Economic Effects of AI Introducing Tinker: Play with AI, bring your ideas to life AI sheds light on an ancient gaming mystery People really hate AI but not as much as Iran—or Democrats | Fortune What is an AI Product Engineer? Phoebe Gates wants her $185 million AI startup to succeed with 'no ties to my privilege or my last name': 'I have a chip on my shoulder' | Fortune
Taskachu — The AI co-founder for solo founders
ndha · 2026-06-23 · via Hacker News - Newest: "AI"

THE AI CO-FOUNDER FOR SOLO FOUNDERSDoesn't sleep, doesn't eat, just shipped

You're not solo
anymore.

MCP-native — agents read and write your boardProject context indexed and reachable from any agentFree forever for solo founders

app.taskachu.com / todaylive preview

backlog3

Auth: Google sign-in flow

Your co-founder doesn't sleep, doesn't eat, and just merged a PR.

Taskachu is the shared workspace Claude, Cursor and Codex all read from and write to — your always-on co-founder.

From thought to ship

Start with a thought.
Ship while it builds.

01

Discover your idea, transform abstractions to knowledge base

Half-sentence in. Brief, decisions, and acceptance criteria out. Your project memory grows with every drop.

02

Generate a backlog and execute with your favorite AI coding tool

Tasks decompose, prioritise, and flow straight into your development workflow with full context attached.

03

Run marketing while the product is being built

Creatives, content, launch prep — drafted in your voice in parallel with the build, not after it.

01Key features

One system. One context.
One execution loop.

Eight primitives, one continuous loop. Each surface is built around the same idea: keep your AI in context, and keep your hands on the keyboard.

01 · IDE execution

Direct execution in your IDE.

Send tasks with full context directly into your development workflow. Brief, decisions and linked docs travel with the task — the first response is already on-spec.

MCP● connected · taskachu

@context · 12 docs · 3 decisions

handoff · TKA-031 · Stripe checkout

Claude Code · session ready

MCPConnected

02 · Knowledge base

Knowledge that compounds.

Markdown docs with hierarchy and a BlockNote editor. Decisions, briefs, runbooks, brand notes — written once, retrieved by every agent you delegate to. Stop pasting from Notion every morning.

📁architecture · 12 pages

@decisions · 2026-q2-stack

@runbooks · incident-response

@brand · voice + tone

MarkdownHierarchical

03 · Smart backlog

Always the right next task.

Ideas decompose into tasks automatically. The AI ranks impact vs. effort and surfaces what to ship today.

P1 · Top pickToday

04 · Handoff context

Everything your AI needs, already in context.

Every handoff to Claude carries the task, the linked docs, and the decisions that shaped it — so the first reply is already on-brief.

Auto-contextOn by default

05 · RAG · Ask Taskachu

Your AI never forgets
your startup.

Workspace-scoped retrieval over every doc, card and decision. Ask Taskachu in-app or reach the same RAG from Claude Code / Cursor over MCP — no copy-paste.

@docs/pricing.md · chunk_07

@decisions/2026-04-stack.md

06 · DevOps · auto

Every task is validated and shipped.

Every completed task triggers your pipeline. Failures route back to the AI with the full trace — most fix themselves before you notice.

CI greenDeploying

07 · Marketing · AI

Marketing while you build.

Creative briefs, content calendars, launch campaigns — drafted in your brand voice and queued to your channels.

ContentCreative

08 · Env & secrets

Structured environments your AI understands.

API keys, environments and rotation, with a clear structure your AI can reason about without ever seeing the values.

DEV● ready

STAGE● ready

PROD● rotate · 12d

Features don't ship products. Taskachu do.

Drop in your first idea — Taskachu turns it into a backlog and hands the top card to Claude in under a minute.

Hand off your first ticket →

02The loop

Continuous execution.
Not task management.

Five steps that keep going. You drop in a thought. Taskachu plans it, helps you build it, checks it works, then helps you tell the world. And then it asks what's next.

Step 01

Capture the idea

Drop in an abstract thought. Get back a structured knowledge base — problem, solution, app architecture and marketing plan. Everything you need to launch a new product.

Step 02

Plan with AI

The backlog re-ranks itself by impact. Top of the list is always today's right move.

Step 03

Hand off to Claude

Send the task, the linked docs and the decisions to your AI coding tool or IDE. One click, full context.

Step 04

Review · close

Code is built. Review and test it. If it's good, close the task. Notes flow back into the knowledge base.

Step 05

Plan what's next

The backlog updates with what you shipped. Tomorrow's right move is already on top.

Your startup moves forward
even when you don't.

Take a walk. Read your kid a bedtime story. Sleep in.
The loop keeps running.

1workspace

instead of seven tabs

MCPnative

direct to Claude Code

RAGbuilt-in

your docs, always in context

$0/ mo

free for solo operators

Built with itself

I cleared a 120-task backlog in 30 minutes —
building Shally with Taskachu.

Last Tuesday I opened my own Backlog board, asked Claude Code to pick the top priorities, and handed each card off over MCP with full context attached. Thirty minutes later, the entire 120-task backlog had moved into Complete. Auth fixes. A pricing tweak. The PWA manifest. The very landing section you're reading.

No prompt re-typing. No tab-juggling. The loop just ran.

Andrii Nadosha — building Shally with Taskachu

Taskachu Shally board with a 120-task backlog cleared into Done in one session

120
cards · Backlog → Done

~30 min
one session

1 operator
0 teammates

120 cards in 30 minutes isn't a flex. It's a Tuesday.

Open a workspace, plug Claude over MCP, ship your own backlog before lunch.

Ship your own backlog →

You are not lacking tools.
You are lacking execution.

03Why Taskachu

Three reasons
to switch.

Bring your existing work with you.

Import from Linear, Jira, Notion, Asana, Trello, GitHub Issues — or a plain CSV. Nothing left behind.

01

Ship without a team.

One workspace for backlog, docs and AI handoffs. You operate — the loop runs.

02

Always the right next thing.

The backlog re-ranks itself. Today's top card is today's right move.

03

Context, never re-explained.

RAG + MCP let every agent read your docs, decisions and board. No paste-and-pray.

04Vs. the stack you'd otherwise glue together

One loop.
Not seven tabs.

Capability

Taskachu

Linear · GitHub · Buffer · ChatGPT

Backlog auto-prioritisation

Direct Claude Code handoff (MCP)

Knowledge base in handoff payload

Marketing & launch drafts

Tools to context-switch between

1

7+

Scales solo → small team

Migrate or duplicate

A1

No context switching between tools

One workspace. One brain. Everything stays where it was.

A2

Consistent execution

No manual overhead. The AI doesn't forget the convention you set last week.

A3

Faster iteration

Idea → plan → handoff in minutes. Less time wiring tools, more time deciding.

A4

Your product memory, always available

Architecture, decisions and brand voice — recalled, not re-explained.

A5

Scales with you

Solo today. Three teammates next quarter. Same workspace, same loop.

06Pricing

Hire your first co-founder
for $12 / month.

Solo is free forever. Upgrade to Team when you need more boards, teammates, RAG documents, and a co-founder that never sleeps. Start with a 7-day trial — no card required.

Free

Solo

For founders who want to test the loop without committing.

$0forever · no card

  • Up to 5 workspaces
  • 1 board per workspace
  • Up to 3 members per workspace
  • 10 documents indexed in RAG
  • 1,000 AI requests / month shared across workspace
  • Slack & GitHub integrations
  • Import from Linear, Jira, Notion, Asana, Trello
  • Custom fields
  • Marketing block
  • Tickets indexed in RAG

Recommended

Pro

Team

Everything in Solo, plus the Pro-only modules.

$12/ month per workspace · billed annually as $144

  • Unlimited workspaces
  • Up to 50 boards per workspace
  • Up to 25 team members per workspace
  • Up to 500 documents indexed in RAG
  • Up to 2,500 tickets indexed in RAG
  • Up to 10,000 AI requests / month shared across workspace
  • Up to 25 custom fields per workspace
  • Up to 10 marketing spaces
  • Priority support

Free forever for solo · 7 days of Pro on the house, no card

Stop dragging tasks.
Start building your startup.

Drop in your first idea, watch it become a backlog, and hand the first task to Claude over MCP — all in one workspace.

Taskachu mascot

07FAQ

Common questions

What is Taskachu?

Taskachu is an AI-native productivity app for solo founders. You manage projects on Kanban-style boards, and AI features (built into the app) help you decompose tasks, prioritise the backlog, run standups, and answer questions about your own workspace. Every AI feature is also reachable from Claude, Cursor, or Claude Code through the Model Context Protocol (MCP), so your AI agent can read and write the same board you do.

Who is Taskachu for?

Solo founders, indie hackers, and small teams (up to ~10 people) who use AI as part of their daily build loop. If you find yourself re-explaining your roadmap to ChatGPT every session, Taskachu replaces that friction with persistent state your AI can read directly.

Does Taskachu work with Claude / Cursor / Claude Code?

Yes. Taskachu exposes a Model Context Protocol (MCP) server at app.taskachu.com/api/mcp. Generate a workspace-scoped Personal Access Token in Settings → API Tokens, paste the snippet into your Claude Code, Claude Desktop, or Cursor config, and your AI agent can list, create, update, move, and delete cards and documents in that workspace — same surface you use in the UI.

How much does Taskachu cost?

Free tier covers one workspace with a capped monthly AI quota — plenty for an early-stage solo project. Pro is $12 per month, includes higher AI quotas, multiple workspaces, and a 7-day free trial with no credit card required.

Can I import tasks from Jira, ClickUp, or Confluence?

Yes. Each workspace has an Imports section that accepts Jira XML exports, ClickUp CSV / JSON, and Confluence HTML / ZIP exports. Imports are two-step: analyse first to see what will be created, then execute when you're happy with the plan.

What AI features are built into Taskachu?

Task decomposition (turn a card into subtasks), card prioritisation, brainstorm sessions that synthesise into board structures, daily standup planning with conversational follow-up, weekly retrospective generation, agent-export packets for handing a card or board to an external code-gen tool, and Ask Taskachu — a workspace-scoped retrieval-augmented assistant that answers questions about your own cards and uploaded documents.

Can I delete my account and all my data?

Yes. Go to Settings → Account → Delete account. We send a confirmation link to your email; clicking it permanently removes your account, every workspace you own (with cascade to all boards, cards, documents, and integrations), and cancels any active Stripe subscriptions. The process is irreversible by design.