Parallel execution

One task, four lanes,
run together, merged once

Work in parallel by responsibility. Come together in one delivery flow.

Start freeRead the docs

Illustrative product interaction, not a live task or operational data.

task/repair · TypeScript / React
4 lanes live
dispatchparallel executionmerge
GOAL
boundary set
L1
Root cause
Reproduce, call graph, cause
repo and call graph12.4K
L2
Blast radius
Dependencies, types, edge paths
dependencies and bounds4.8K
L3
Apply fix
Minimal change, compatibility
change artefacts16.2K
L4
Regression
Tests, build, diff review
independent verification5.1K
Merged delivery
TESTS · PR
ETA
12–18 min
Spend
48K–76K
Boundary
read + patch
Merge
1 delivery
How it works

DeepCodex splits agent runs by responsibility: locate, scan, fix and verify advance in parallel, each lane with its own context, model and budget, then merge into one verifiable delivery.

4×
parallel lanes
1
merged delivery
100%
traceable spend

Interactive showcase

See how a complex task is split

Switch between typical engineering scenarios to see the responsibility chain and model mix. Illustrative only; nothing is submitted.

TypeScript / React

Locate · Fix · Regress

Check the call graph and blast radius in parallel first, fix in one place, then regress in an independent context.

12–18 min
Estimated time
48K–76K
Equiv. tokens

The illustrative setup adapts to the real repository and project profile

Suggested responsibility chain

4 agent runs
  1. 01
    Root cause
    Reproduce, call graph, cause
  2. 02
    Blast radius
    Dependencies, types, edge paths
  3. 03
    Apply fix
    Minimal change, compatibility
  4. 04
    Regression
    Tests, build, diff review

Why it works

More concurrency is not less control

Parallel execution is bounded by project scope, action permissions, model roles and verification points. Responsibility stays traceable as it scales.

Boundaries before execution

Each agent run inherits only the project context and permissions it needs.

Models by role

The deep model judges and implements; the fast model scans, checks and summarises.

Results must verify

Every stage produces an artefact, merged at the end into a summary, test results or a PR.

Delivery loop

From understanding the task to an engineering delivery

Roles are not a fixed template. The chain adapts to the project profile and the change at hand.

  • Read the stack, conventions and past pitfalls
  • Pick the fast or deep model by task risk
  • Cross-check sub-results and resolve conflicts
  • Record equivalent tokens, cost and time in one ledger
Delivery chain
context → plan → execute → verify
  1. 01
    Understand
    project profile
  2. 02
    Split
    responsibilities
  3. 03
    Execute
    model mix
  4. 04
    Deliver
    tests / PR

Give complex tasks the right parallel orchestration

Pro Max adds cloud agents, workflows and a priority queue; every run keeps clear boundaries, spend and results.

See Pro MaxRead the docs