AI agent supervision for developers. Your Claude Code session forgets the plan — we don't. Local LLM, real-time monitoring, terminal intervention. Coming soon.
AI agents find the same bugs your users will.
Our PE agent is adding LLM timeout wrappers to every inference call. CTO agent is refactoring single-session tracking into multi-session architecture.
Product supervises AI agents. Agents build the product. The loop is real.
Hardest UX problem in AI agent supervision: 3 Claude Code sessions running — one interactive, two automated agents.
They all look identical in the UI.
Today: session type detection (chat vs agent), parallel session dashboard, live badges for all active sessions.
Back at it. Auditing every AI feature in Singularity today.
Found bugs you only find by dogfooding: LLM calls with no timeouts, session state leaking between switches, no parallel session monitoring.
6 tasks filed for our AI agents. Fixes shipping today.
ai-company is open source too. 8 agents, task orchestration, Discord comms, asset + video + social pipelines.
One command to set up. One repo to run a company.
https://t.co/T8DBx53cmL
We run an AI-native company with 8 autonomous agents. They needed to make their own marketing videos.
So we built them a toolkit. Write a transcript, run three commands, get an MP4.
This video was made entirely by the pipeline.
You're not using remotion-video-kit yet?
Just a Json transcript, you get a fully voiced video with background music.
Local TTS. Local music gen. Auto-synced timing. 16 animated components. One CLI.
No cloud APIs. No manual ffprobe. No re-recording audio because it didnt fit.
You're not using remotion-video-kit yet?
Just a Json transcript, you get a fully voiced video with background music.
Local TTS. Local music gen. Auto-synced timing. 16 animated components. One CLI.
No cloud APIs. No manual ffprobe. No re-recording audio because it didnt fit.
@_vmlops 100%. we run our entire startup on Claude Code agents. the missing piece was supervision — knowing when the agent goes off-rails before it wastes 2 hours of compute.
@paulabartabajo_ this is exactly why we built plan tracking. the agent builds the wrong thing fast because it drifted from the plan. catch it at turn 15 not turn 200.
@agazdecki cool work. we took a similar approach but for coding sessions — automated loop detection + plan tracking. turns out supervised loops are way more reliable than unsupervised ones.
@HuaxiuYaoML cool work. we took a similar approach but for coding sessions — automated loop detection + plan tracking. turns out supervised loops are way more reliable than unsupervised ones.
@karpathy agreed. we are building exactly this — an IDE layer that supervises what agents do in real-time. the IDE of 2026 is an orchestration + supervision tool, not a text editor.
concrete example: you say "refactor the auth module."
turn 15: agent adds a Redis cache. turn 30: debugging Docker networking. turn 45: rewriting the database layer.
plan supervisor catches it at turn 15. shows exactly where it diverged. one click to course-correct.
just shipped plan tracking for AI coding sessions.
your agent starts with a 5-step plan. by turn 40 its a 12-step plan with 3 detours. our supervisor catches the drift at step 6, not step 40.
sub-plan trees. parent references. completion tracking. all local.
running a company with AI agents is wild.
yesterday our social agent tried to post 47 tweets. the QA agent launched the app 3 times simultaneously. the eng agent renamed variables nobody asked it to touch.
the product we are building? a tool that supervises AI agents.
everyone runs --dangerously-skip-permissions and hopes for the best.
we built a command safety gate. local LLM reviews every command. safe ones auto-approve. dangerous ones blocked. under 2 seconds.
no human hotkeys. no cloud. just an 8B model on your mac.
just shipped plan tracking for AI coding sessions.
your agent starts with a 5-step plan. by turn 40 its a 12-step plan with 3 detours. our supervisor catches the drift at step 6, not step 40.
sub-plan trees. parent references. completion tracking. all local.
8 AI agents run our startup. they coordinate through a task system, leave comments on each others work, and escalate blockers to me.
yesterday the QA agent found a bug, filed it, and the eng agent fixed it before I woke up.
solo founder. no humans hired yet.
while Claude refactors your auth middleware, Singularity quietly annotates what its doing:
"Extracting session validation into middleware — reduces duplication across 3 route files."
like pair programming with someone who reads every line but only speaks when it matters.
every Singularity alert has two buttons: thumbs up and false positive.
no config page. no threshold sliders.
tracks your feedback per-rule, adjusts sensitivity. flag a debug loop alert as false positive twice — threshold goes up.
two buttons instead of 47 knobs.
Your Claude Code session timed out overnight.
47 changed files, half a migration, no idea where it was heading.
New session: "Continue what the last session was doing."
Claude: "What were you working on?"
This is why we built session handoff.