Armagan Amcalar

This account is verified. Learn more

@dashersw

Founder @Coyotiv, CTO @openservai

Software architect, leader, lecturer, public speaker, mentor, entrepreneur, electronics engineer, guitarist, singer.

Berlin, Germany coyotiv.com Joined February 2009

566 Following 9.2K Followers 12K Posts

Latest posts 5

Pinned post

Armagan Amcalar @dashersw Dec 19, 2025

It’s been 15 years since I last wrote an academic paper and I didn't expect the next to be this fundamental.

Today we published a research paper with @openservai that represents a major breakthrough in how we think about AI reasoning.

For years, we’ve been told that better AI reasoning means bigger models, longer chains of thought, and higher costs. We accepted that trade-off almost by default.

This work questions that assumption.

With BRAID's structured, bounded reasoning, we’re seeing up to 74× efficiency gains and ~30× better performance per dollar without losing accuracy.

Armagan Amcalar @dashersw 5d

Super excited to see what developers build this time with SERV Reasoning and the new tracks from @dphnAI, @GoKiteAI and @reppo

We’re also getting great feedback on Graph Sharding from early SERV builders and enterprise AI developers, and incorporating it as we work toward the wider SERV v3 release. Cooking hard!

OpenServ @openservai 6d

SERV Hackathon 02 is live.

Build with SERV Reasoning + @dphnAI, @GoKiteAI, @reppo or bring your own idea to the Open Track.

Two weeks to cook across AI inference, agentic payments, AI data markets, and more.

Start here: openserv.ai/hackathon-2

View quoted post on X

Armagan Amcalar @dashersw Oct 29

We’ve been building SERV technology block by block for years now and it all led up to SERV v3. With SERV v3, we focused on reliable, consistent, observable execution of autonomous AI agent workflows.

Fixed logic, bounded decisions, and open-ended reasoning each need a different approach. Getting those boundaries right is the engineering challenge behind making complex workflows more controllable as they grow.

I spent a lot of time walking through real tasks with developers. Those conversations have been an important part of this work. They help us understand how teams structure their workflows, where they need more control, and how they want to improve them.

We’ve opened the beta to a select cohort of builders, and I’m excited to see how they use Graph Sharding in their own systems.

At @openservai, we’ll be sharing more in the coming weeks about the state of enterprise AI, what it takes to build better reasoning for agents, and what we’re learning from developers as we work toward the wider SERV v3 release.

OpenServ @openservai Oct 29

The next major leap for SERV Reasoning is coming with SERV v3: Graph Sharding.

We’re preparing the next builder cohort to test it, building on feedback from the first beta users as we move toward a wider release.

In this walkthrough, our CTO @dashersw talks with builders and shows Graph Sharding in action, exploring how teams can inspect an agent workflow, spot drift, and see how a change at one step affects everything downstream.

That visibility gives developers more ways to understand, refine, and scale their AI workflows. Builder conversations and tests are helping us push Graph Sharding toward production, with more control over how complex workflows run.

We’re building SERV Reasoning for enterprise AI, the agentic economy, and the next wave of AI applications.

Apply to join the next beta builder cohort and help shape Graph Sharding: openserv.typeform.com/graphsharding

View quoted post on X

Armagan Amcalar @dashersw Oct 27

Last week I sat down with Akar from Neol to talk about AI reasoning, decision models, and why current agent systems still fall short of enterprise and government expectations.

We also tested Graph Sharding, a feature in @openservai’s upcoming SERV v3 release on 3-4 real prompts. Some steps written as English prose could be handled directly with scripts and decision nodes. Graph Sharding routes workflow steps through the node types they need, including script, decision, and agent nodes.

In one run, a production task that took 7 seconds as a single LLM call took 2.5 seconds with Graph Sharding. That’s one result from a small set of prompts, not a benchmark, but it shows how the execution path can affect latency.

We’ll share more from the developer conversations soon. Graph Sharding beta access starts rolling out this week to a limited group of existing builders. Looking forward to seeing what they build with SERV.

Armagan Amcalar @dashersw Oct 23

SERV payments live. SERV payments live.

OpenServ @openservai Oct 23

The next stage of SERV Reasoning is coming together.

- SERV payments live
- Next hackathon brings more AI teams and builders
- Enterprise AI development and distribution moving forward with AWS Marketplace first

Graph Sharding will enable inspectable reasoning, greater control over AI agent workflows, and near-zero-cost decisions to the agentic economy.

v3 beta will open next week to a limited cohort of existing SERV builders: public launch is targeted for November.

View quoted post on X