AlgorithmShift

Platform

Thirteen specialist agents. Three phases. One graph.

Every agent owns a slice of the delivery pipeline and hands off by typed contract. Pick a phase to dive into the agents that power it — or see all thirteen at a glance on the handoff graph below.
Typed contractsTier-matched costAudited tool useHuman-gated reviews
Book a demoSee the orchestration graph
agents · handoff graph
requirementstasksdesignschemaintegrationpagesmigrationsdebugtestssecurityrelease-notesreviewmaster-merge
planbuildship

The problem

A single "build-everything" AI is easy to prompt and impossible to trust. AlgorithmShift factors the work into thirteen narrow agents across three phases, each tuned to the cheapest model that can handle its job, each callable in isolation, each auditable. You pay for what you use and trust what you ship.

The three phases

Pick a phase to see its agents.

Phase

4 agents

Plan

Capture intent, break it into tasks, gate with review.

  • requirements
  • tasks
  • review
  • master merge
Explore plan agents

Phase

6 agents

Build

Design tokens, schema, pages, migrations, integrations, and debug.

  • design
  • schema
  • pages
  • migrations
  • integration
  • debug
Explore build agents

Phase

3 agents

Ship

Release notes, audit trail, master-spec rollup.

  • tests
  • security
  • release notes
Explore ship agents

13

Specialist agents

plan · build · ship

3 tiers

Haiku · Sonnet · Opus

cheapest that fits the job

Typed

Contracts at every handoff

no freeform prompt chaining

Audited

Every tool call logged

SIEM-ready out of the box

FAQ

Common questions

Why multiple agents instead of one?
Specialisation lowers cost (cheap models handle narrow jobs), raises quality (each prompt is tuned to its task), and keeps the blast radius of a failure small. Parallelism is a side benefit — independent agents run concurrently.
Can I customise an agent's prompt?
System prompts are read-only for safety, but you can attach workspace-level context (glossary, voice samples, domain notes) that every agent threads into its own prompt. For fully custom behaviour, use the Agent Builder to author a new agent.
Do agents share memory?
No — agents communicate only via typed artifacts. This makes every handoff traceable and every agent replayable in isolation. If you need shared state, it lives in the workspace as a first-class artifact.
Which model powers each agent?
Most agents run Sonnet by default with Opus escalation on parse/validation failures. Cheap tasks (tasks, migrations, integration, review) run Haiku. Enterprise customers can route individual agents to their own hosted models.
How are agent updates rolled out?
Every agent is versioned. Workflows pin agent versions so improvements don't surprise live pipelines — you opt in per workspace. Changelogs ship with each release.

See the graph run end-to-end.

Bring a real requirement. Watch the agents hand it off — plan to build to ship.

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