Agentic workflow map

The human toolchain can be turned into a staged AI workflow.

The key idea is simple: do not ask one agent to "do everything." Split the job into stages with clean artifacts, clear handoffs, and a small number of tools per step.

Inputs, outputs, artifacts Tool choice per stage Last verified: April 4, 2026
Stage map

One good agent flow is a chain of small, checkable steps.

01

Author RTL and tests

Inputs: spec, interface notes, examples

Outputs: RTL files and a testbench

Artifacts: `.sv`, `.v`, testbench source

Tool: editor, lint, repo context

Agent responsibility: produce small, reviewable source changes and explain assumptions.

02

Choose the simulator

Inputs: language features, desired speed, platform

Outputs: selected sim path

Artifacts: command plan

Tool: Verilator or Icarus Verilog

Agent responsibility: pick the smallest tool that fits the design and explain why.

03

Run compile and simulation

Inputs: RTL, testbench, compile flags

Outputs: logs, executable, pass/fail result

Artifacts: build logs, `obj_dir/`, simulation binary

Tool: Verilator or Icarus

Agent responsibility: run commands, capture logs, and isolate the smallest failing step.

04

Collect traces and logs

Inputs: simulation outputs

Outputs: trace files and summarized findings

Artifacts: `.vcd`, `.fst`, text logs

Tool: simulator trace output

Agent responsibility: keep the raw artifacts, then summarize what matters.

05

Triage failures

Inputs: logs, waveforms, expected behavior

Outputs: likely bug class and next fix

Artifacts: issue notes, patch candidates

Tool: GTKWave plus source inspection

Agent responsibility: connect a failing signal pattern back to the responsible RTL or testbench code.

06

Synthesize with Yosys

Inputs: RTL that already simulates

Outputs: netlist or synthesis stats

Artifacts: JSON netlist, logs, area/timing summaries

Tool: Yosys

Agent responsibility: run the chosen script, save outputs, and report what changed compared with the RTL-level intent.

07

Branch to FPGA or ASIC backend

Inputs: synthesized design, target platform

Outputs: route, timing, or bitstream path

Artifacts: P&R outputs, timing reports, bitstreams

Tool: nextpnr/openFPGALoader or OpenROAD/OpenLane/OpenSTA

Agent responsibility: select the backend path based on target hardware, not by default habit.

Why this works well for agents
  • Each stage has a small tool surface area.
  • Each stage emits real artifacts that can be checked and reused.
  • Failure analysis becomes easier because the handoff points are explicit.
  • The same structure works for CI and for human review.
Natural link to the workflows hub

This toolchain page complements the AI workflows sub-portal: the workflows hub explains how to structure agentic reasoning, while this page shows how that structure maps onto real open-source hardware tools and artifacts.