E2e test updated to verify: virtual office sidebar toggle, Composio
Tools settings tab visibility, and @mention with canonical handles.
New integration test verifies that a human reply in a thread wakes
agent participants without requiring explicit @mentions.
MentionTextarea inserted raw agent names (e.g. @Sarah Chen) but the
backend regex captured only the first word (@Sarah), causing mention
resolution to fail silently. Moved canonicalMentionHandle to shared/
so the renderer can produce space-free handles that the backend resolves
correctly.
The GPT-account (Codex) path supports tool calls and worked before; my
forced tool_choice broke it and was the wrong fix. The real regression was
strict:null in the rebuild's tool definitions, which made the endpoint drop
the tool list so the model had nothing to call — a "Done" run that hired no
one. Forcing then turned that silent failure into a red one.
Restore the original "auto" loop (no forced tool_choice, no finish tool) and
keep only the one-line strict:null omission. Codex now receives valid tools
on the working "auto" choice, as in the version that worked.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Forcing only the opening turn let a weak model take one token action and
stop, so a kickoff hired one agent (or none) and went quiet. Now every turn
is forced (tool_choice required) and the agent ends only by calling the new
`finish` tool — so it must keep hiring, delegating, and messaging until the
work is actually done. Finishing with zero actions, or returning no tool
call at all, fails the run loudly instead of faking success.
Prompts tell each agent it must call a tool every turn and finish only when
done. Tests drive weak-model stubs that act then finish, proving a full team
forms rather than a single gesture.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
The whole premise is cheap models + skills + a team — so the control plane,
not the model, must guarantee action. Every adapter hardcoded
tool_choice:"auto", letting a weak model answer the kickoff with prose and
"succeed" having hired no one, delegated nothing, and said nothing.
Now the agent loop compels a tool call on the opening turn (tool_choice
plumbed through every backend: OpenAI/Responses/Chat, Anthropic, Codex,
Copilot, Azure, Custom, Gemini ANY mode, Bedrock any). If the forced turn
still yields no tool call, the run fails loudly instead of recording a
deceptive success — surfacing the problem (let it crash) rather than a
silent dead company. After it has acted, the model chooses freely.
Tested: a stub that rambles on "auto" but acts when forced now posts a
kickoff message; a prose-only first turn fails the run.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Audit of the "agents barely communicate / nothing runs" reports: the
bootstrap run, hiring, delegation, channel messages, file handoffs, and
heartbeat continuation are already covered by autonomous-run.test. The one
untested link was the round trip — an @mention actually waking a teammate
who then replies. This test drives a scripted CEO that hires an engineer
and @mentions them in #engineering, asserts the mention created a queued
chat_mention run for that engineer, executes it, and confirms the engineer
replies inside the same thread (two senders, one thread). The orchestration
is sound; real-world silence is a function of the model's tool-use, not the
control plane.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
A goal created from the Work page only wrote a goals row; nothing ever
read it, so the company never started working on it. Creating a goal now
produces an "Operationalize goal" kickoff task for the chosen owner (or
the top-level agent when unowned) and re-enables that agent's heartbeat,
so the autonomous queue worker starts the run - the same activation
contract the previous runtime had via goal_activated wakes and CEO
bootstrap. Onboarding shares the same kickoff module instead of its own
copy.
The queue worker now also enqueues one run per actionable assigned task of a
heartbeat-enabled agent with an enabled provider and no run yet, so after the
CEO hires and delegates, its reports start their tasks on their own. Each task
is enqueued at most once. The team-building prompt is now scoped to managers
(no manager) with an empty team, so reports execute their task instead.
The new app reached a real LLM but never ran an agent: the kickoff task_run
sat queued forever and runTask was a single text completion with no tools.
This adds the missing runtime:
- provider-tool-turn: OpenAI Responses + Anthropic Messages tool-use turns
- agent-tools + deliverable-writer: hire_agent, create_task,
update_task_status, write_deliverable (workspace-scoped, traversal-safe)
- agent-run-loop: real tool-use loop, capped iterations
- task-queue-worker: claims queued runs in a transaction and executes them
task-execution now drives the loop; a background worker auto-runs the
bootstrap CEO run so it hires its team, delegates tasks, and writes the first
deliverable into the bound workspace. Autonomy is gated by AGENTCOMPANY_NEW_AUTORUN
(tests run with it off to stay hermetic).
ZacharyZhang-NY
