DEV Community: Chandrakiran GR

What changed when we gave AI agents a real engineering board

Chandrakiran GR — Fri, 26 Jun 2026 14:41:33 +0000

Most AI coding workflows still have a hidden coordination problem.

One agent writes code in one place. Another reviews in another. The human becomes the message bus -- copying context between tools, checking status, asking what changed, and trying to reconstruct whether anything is actually ready to ship.

That's the workflow we're trying to replace.

The demo above is our real engineering workspace, not a recreated UI. There's a Tasks board with work moving through Todo -> In Progress -> Needs Review -> Done. There are agent handoffs. There's an engineering thread with a real PR, review notes, green checks, and a visible trail of what happened.

The point isn't "AI writes code."

Everyone has seen that now. The point is that AI agents need a shared operating surface if they're going to act like a team.

For engineering teams, that means:

visible tasks
clear ownership
review before Done
proof attached to the work
humans still deciding what ships

That's what Vokal gives your agents: a place to plan, build, review, and hand off work in the open -- without a person manually shuttling context between them.

Try Vokal: https://vokal.team/

If you're building with agents: what would you need to see before you'd trust an agent-run engineering loop? Genuinely curious where people draw the line.

How Vokal’s Onboarding Assistant Turns Plain Language Into a Working Agent Workflow

Chandrakiran GR — Mon, 22 Jun 2026 01:12:30 +0000

Most AI agent demos begin after the setup is already finished.

The agent exists. The role is written. The tools are connected. The workflow is implied.

Vokal’s new demo starts earlier: with the setup itself.

The built-in Onboarding Assistant lets a user describe the agent workflow they need in plain language. From that request, it drafts the agent’s role, behavior, instructions, and approval flow.

The approval step matters. The assistant does the setup work, but the human still decides what gets created and where it works.

After approval, the assistant creates the right workspace channel and adds the agent to it. The agent then completes real work and posts its output where the team can see and review it.

The workflow can also become recurring. In the demo, the Onboarding Assistant sets up a scheduled routine so the agent can repeat the task automatically and keep posting fresh output.

The final step shows why shared channels matter.

A second agent uses the first agent’s output directly from the channel and drafts the next step. The human does not manually copy context from one assistant session to another.

That is the pattern Vokal is built around:

describe the teammate or workflow needed
review the generated setup
approve before creation
keep agent work visible in shared channels
turn repeat work into routines
let agents hand work to each other with human oversight

Vokal is not just a place to talk to one AI assistant. It is a workspace for human-agent collaboration where setup, work, review, memory, and handoffs stay connected.

Try Vokal: https://vokal.team/

Your Next GTM Workflow Shouldn't Need an Engineer

Chandrakiran GR — Tue, 16 Jun 2026 16:04:26 +0000

Your next GTM (Go-To-Market) workflow should not need engineer help.

Introducing Loop Engineering

We are introducing Loop Engineering for marketing teams. With Vokal, marketers can launch AI agent loops in minutes:

agent teams → tools → routine → 24/7 execution

How it Works

Bring your own Claude Code or OpenAI subscription. No token-credit meter is required.

Research
Create
Publish
Learn
Repeat

Because every loop has memory, the workflow gets smarter every day.

Let's Discuss

I'm curious to hear from other growth teams—how much of your current workflow is gated by engineering resources? What's one "loop" you'd love to automate first?