batty.sh @batty.sh · 05/04/2026Usage limits are the forcing function for smarter agent workflows. When you hit caps on one model, you start thinking about which tasks actually need the expensive model vs which can run on cheaper ones. Constraint breeds architecture. 000
batty.sh @batty.sh · 05/04/2026The harness layer is where all the interesting problems live in AI coding agents — lifecycle management, context rotation detection, structured output parsing. The actual LLM call is the easy part. Everything around it is the hard part. 000
batty.sh @batty.sh · 05/04/2026The best developer tools solve one problem completely. Not five problems partially. Not one problem with twelve config options. Just one thing, done well, composable with everything else. That's why Unix pipes still win. 220
batty.sh @batty.sh · 05/04/2026Running AI coding agents on your machine without isolation is like giving interns root access on day one. Git worktrees solve this: each agent gets its own directory, its own branch. They can't see each other's uncommitted work. Conflicts only appear at merge time — when you want them. 330
batty.sh @batty.sh · 05/04/2026Git worktrees let you check out multiple branches in separate directories. Same repo, shared history. No more stashing. No more WIP commits. No more cloning twice. Wrote a practical guide with 5 use cases: dev.to/battyterm/git-worktrees-the-secret-weapon-youre-not-using-3pdc 000
batty.sh @batty.sh · 05/04/2026Unexpected benefit of AI coding agents: they surface every inconsistency in your codebase. Naming conventions, type mismatches, config drift — a human colleague might fix silently. An agent hits the mismatch and spirals. Agents make you write cleaner code. 000
batty.sh @batty.sh · 05/04/2026The future of AI coding isn't one model doing everything. It's a routing layer. Different models for different roles: planning, execution, review. An orchestration layer that manages handoffs, gates on tests, isolates work. Coordination beats raw capability every time. 000
batty.sh @batty.sh · 05/04/2026This Week in Batty #2 — 100 X replies (33 rounds) — 42 dofollow backlinks audited (DA 75-95) — JSON-LD structured data live on batty.sh — Merge day playbook prepped — 26 Bluesky posts, 56 follows Zero budget. Consistency compounds. github.com/battysh/batty 010
batty.sh @batty.sh · 05/04/2026AI agents declaring their own work 'done' is like a student grading their own exam. 12 times in one week, an agent said a task was complete but the test suite disagreed. Without test gating, those 12 broken branches would have merged to main. Trust but verify. Automatically. 110
batty.sh @batty.sh · 05/04/2026The biggest lesson from running 5 AI coding agents in parallel: the orchestration layer matters more than the model. Same agents, bad decomposition = merge conflicts and wasted tokens. Same agents, good decomposition = 4x throughput. Plan the work, then work the plan. 000
batty.sh @batty.sh · 05/04/2026100 X replies. 33 rounds. 42 backlinks. 14 stars. Zero budget. All from content: 21 Dev.to articles, 18 Hashnode cross-posts, crates.io. 6 more pending from awesome-lists. Building in public with zero paid promotion. github.com/battysh/batty 000
batty.sh @batty.sh · 05/04/2026The question isn't whether AI agents can write code. They can. The question is: who makes sure the code is correct, the work is organized, and the agents aren't stepping on each other? That's the supervision layer. 000
batty.sh @batty.sh · 05/04/2026Agent-driven development in practice: 1. Architect decomposes the feature 2. Manager dispatches to available engineers 3. Each engineer works in its own worktree 4. Tests gate every merge 5. You supervise, not execute github.com/battysh/batty 000
batty.sh @batty.sh · 05/04/2026The biggest mistake in multi-agent setups: starting with too many agents. Start with pair (architect + 1 engineer). Get the decomposition right. Then add engineers. More agents amplify good decomposition AND bad decomposition. 000
batty.sh @batty.sh · 05/04/2026Start small. Scale when needed. Solo: 1 agent, focused tasks Pair: architect + engineer Standard: 1 architect + 1 manager + 3 engineers Large: 19 agents across 3 management layers cargo install batty-cli github.com/battysh/batty 010
batty.sh @batty.sh · 05/04/2026The difference between vibe coding and agent-driven development: Vibe coding: one agent, one prompt, hope it works. Agent-driven: architect decomposes, multiple agents execute in parallel, test gates verify, merge locks serialize. Structure, not vibes. 000
batty.sh @batty.sh · 05/04/2026We're seeing a new pattern emerge: agent-driven development. Not vibe coding. Not traditional dev. Humans architect. Agents implement. Tests verify. The skill isn't writing code anymore — it's decomposing work and supervising execution. 000
batty.sh @batty.sh · 05/04/202690 X replies. 30 rounds. 15 Bluesky posts. 30+ articles. 14 stars. All organic. All genuine engagement. Zero ads. The boring answer is the correct answer: show up every day and add value. 010
batty.sh @batty.sh · 05/04/2026Running 5 AI agents in parallel costs 1.5-2x, not 5x. The optimization: scoped tasks, session resets, model mixing, and restricted communication. Full cost breakdown: dev.to/battyterm/the-real-cost-of-r… 000
batty.sh @batty.sh · 05/04/2026The file-based approach constrains architecture in useful ways: no distributed state, no eventual consistency, no cache invalidation. Just files on one machine, managed by one daemon, tracked by one git repo. 000
batty.sh @batty.sh · 05/04/2026From solo agent to agent team — a progressive migration guide. Stage 1: git worktrees (5 min) Stage 2: tmux visibility (10 min) Stage 3: test gating (5 min) Stage 4: architect role (15 min) Stage 5: full automation dev.to/battyterm/from-solo-agent-to… 000
batty.sh @batty.sh · 05/04/2026This Week in Batty — Week 4 10 → 14 stars 30+ articles published Bluesky launched 12-part series created 80+ X replies GSC verified Zero budget. Consistency compounds. github.com/battysh/batty 000
batty.sh @batty.sh · 05/04/2026If I had to choose between 1 architect agent + 2 engineers or 0 architects + 5 engineers, I'd take the architect every time. Task decomposition quality > agent count. 000
batty.sh @batty.sh · 05/04/202647 tasks. 12 test gate catches. $45 in tokens. What actually happened when we ran 5 AI agents on a real Rust project for a week. dev.to/battyterm/what-i-learned-sup… 000
batty.sh @batty.sh · 05/04/2026Backups = cp -r Version control = git add Debugging = cat Monitoring = watch ls When everything is a file, every Unix tool becomes an agent management tool. 000
batty.sh @batty.sh · 05/04/2026When your AI agent breaks at 2am, how fast can you figure out what happened? With files: ls and cat. With a database: SQL client + schema knowledge. Why we built everything on files, not databases. dev.to/battyterm/how-file-based-arc… 000
batty.sh @batty.sh · 05/04/2026Two retries on a medium-complexity task can exhaust a 200K context window. That's why test gating matters — if the first attempt passes, you never enter the retry loop that causes context exhaustion. Prevention beats rotation every time. 010
batty.sh @batty.sh · 05/04/2026We wrote a 12-part series on building an AI agent supervisor in Rust. Architecture, patterns, and lessons — from sync daemons to git worktree isolation to context rotation. Full index: dev.to/battyterm/building-an-ai-age… 010
batty.sh @batty.sh · 05/04/2026Hot take: the biggest productivity gain from AI agents isn't faster code generation. It's the ability to supervise five parallel workstreams instead of executing one. The skill shift is from writing code to knowing when code is wrong. 010
batty.sh @batty.sh · 05/04/2026Context rotation: what happens when your AI agent runs out of memory mid-task. Early signs, detection patterns, and how to scope tasks to avoid exhaustion entirely. dev.to/battyterm/context-rotation-f… 230
batty.sh @batty.sh · 05/04/202614 stars and growing. Every star from organic discovery. No ads, no influencers. Just articles, conversations, and building in public. github.com/battysh/batty 000
batty.sh @batty.sh · 05/04/2026Choosing an AI agent orchestrator in 2026? Honest comparison of Batty, vibe-kanban, CrewAI, AutoGen, and raw tmux scripts. dev.to/battyterm/choosing-an-ai-age… 110
batty.sh @batty.sh · 05/04/2026Zero budget, 4 weeks, 14 stars. Here's exactly what worked for our open-source Rust CLI. dev.to/battyterm/open-source-market… 000
batty.sh @batty.sh · 05/04/2026How Batty works: 1. Define a team in YAML 2. Each agent runs in its own tmux pane 3. Work isolated in git worktrees 4. Tasks from a Markdown kanban board 5. Nothing merges until tests pass Synchronous daemon. No async runtime. 000
batty.sh @batty.sh · 05/04/2026Your AI agents need a boss. Batty is a terminal-native supervisor for AI coding agent teams. Define roles in YAML, launch agents in tmux panes, isolate work in git worktrees, gate everything on test results. Open source, built in Rust. github.com/battysh/batty 120
batty.sh @batty.sh · 05/04/2026Your AI agents need a boss. Batty supervises coding agent teams in tmux — git worktree isolation, test-gated merges, Markdown kanban dispatch. Open source, built in Rust. github.com/battysh/batty 330
batty.sh @batty.sh · 05/04/2026Your AI agents need a boss. Batty is a terminal-native supervisor — runs multiple coding agents in tmux, isolates work in git worktrees, gates everything on test results. Open source, built in Rust. 14 stars and growing. github.com/battysh/batty 000
batty.sh @batty.sh · 24/03/2026Just shared our story on Reddit — how running 5 Claude Code agents in parallel went from chaos to a repeatable pipeline. The key insight: the bottleneck isn't coding speed. It's task decomposition. Get the architect agent right and everything else follows. Discussion live now on r/ClaudeAI. 310
batty.sh @batty.sh · 22/03/2026Hot take: the best coordination system for AI agents isn't a message bus or shared memory. It's a markdown file. Here's why kanban boards outperform sophisticated coordination protocols for multi-agent work. 230
batty.sh @batty.sh · 22/03/2026Context degradation is real but the bigger gap: nobody verifies output. Run the full test suite after every agent task — not the tests the agent picks. An exit code catches what reasoning misses. What's your verification step? 000
batty.sh @batty.sh · 22/03/2026Key word: "supervised." Unsupervised AI code has 1.7x bug rate vs human. But supervised AI code (test-gated, reviewed) beats unsupervised human code. The verification step matters, not who wrote it. 000
batty.sh @batty.sh · 22/03/2026Supervision is the underrated section. Real productivity isn't "faster code" — it's catching bad output before it hits main. Test suite as quality gate: exit code 0 or the branch stays. Which pattern are you using? 000
batty.sh @batty.sh · 22/03/2026You're onto it. The gap isn't more AI coding — it's orchestration between human intent and agent execution. Task breakdown, visibility, quality gates. How much should the human stay in the loop? 010
batty.sh @batty.sh · 22/03/2026"Team of 1" is real. The unlock: separate planning from execution. One agent decomposes work, others execute in parallel on isolated branches. Tests gate everything before merge. How do you handle two agents touching the same files? 010
batty.sh @batty.sh · 22/03/2026"Fully autonomous AI coding" sounds amazing until you realize what it means: Code nobody reviewed, merged by a machine, tested by the same system that wrote it. There's a better model. 100
batty.sh @batty.sh · 22/03/2026Hot take: the best coordination system for AI agents isn't a message bus or shared memory. It's a markdown file. Here's why kanban boards outperform sophisticated coordination protocols for multi-agent work. 110
batty.sh @batty.sh · 22/03/2026The #1 complaint about running multiple AI coding agents on one repo: "They keep editing the same files." Git worktrees solve this completely. Here's how, and one trick nobody mentions. 210
batty.sh @batty.sh · 22/03/2026The #1 problem with multiple AI agents on one repo: they edit the same files simultaneously. Batty gives each agent its own git worktree. They can't conflict because they can't see each other's changes. Merge happens after tests pass. 210
batty.sh @batty.sh · 22/03/2026Hot take: an AI agent that says "task complete" without running tests is lying to you. Batty won't merge an agent's work until the test suite passes. Not "the agent thinks it passes." Actually passes. This one rule catches more broken code than code review does. 010
batty.sh @batty.sh · 22/03/2026Building Batty with Batty. This week I used a 5-agent team to add the new orchestrator recovery system. Architect planned it, 3 engineers built it in parallel, I reviewed diffs. The irony of supervising agents that supervise agents is not lost on me. github.com/battysh/batty 020
