AGemini 4 Argon
Google DeepMindStrong on paper. Unguided, it rushes into execution. With AEO, it gets close to Opus on coding tasks.
Free webinar · Thu, Oct 29 · Registration open
Mecha AI / Claude vs Argon
Same model.
Better method.
A free live webinar on one instruction file that changes how Gemini 4 Argon runs coding tasks - until its results stand next to Claude Opus 5.5. We work on a real project live, so you see the before and after for yourself.
Thu, Oct 29Online & liveFree to attend
29.10Thursday · free live webinar, online
01complete AEO instruction file for every registrant
02runs on the same project - before and after guidance
06stages, from understanding the task to testing the result
01 / The gap
The intelligence is there.
The intelligence is there.
The plan isn't.
Hand an agent a big task and it often rushes straight into code - without exploring the project, without picking the right tool, stacking each step on guesses nobody checked. That distance between what a model can do and what it actually delivers has a name: the Execution Strategy Gap.
You'll leave knowing how to make a model decide when to search, when to reuse an existing solution and when to build from scratch - and how to work in stages, verifying each one before moving on.
Without guidance
With AEO
Starts coding from the first message
Defines the goal and success criteria first
Assumes how the project works
Explores files and structure before touching anything
Reinvents what already exists
Decides: search, reuse, or build
Ships everything in one go
Splits the work into checkable stages
Builds on untested assumptions
Tests each stage before the next one
Says “done” and hands it over
Fixes from test results, not guesses
02 / The contendersSame tasks · same project · same success criteria
ABClaude Opus 5.5
AnthropicThe benchmark. The exact same task and success criteria, so the call is fair.
Argon77.9%
Opus 5.574.2%
Real-world software engineering tasks, as reported by Google.
output tokens in a single response - built for long, multi-step work.
Gemini 4 Argon was announced on September 30, 2026. The figures above are Google’s own, on benchmarks Google chose, and haven’t been independently verified. We don’t lean on them - we show our own runs, live.
03 / The method · AEONot a prompt.
Not a prompt.
An execution method.
Agentic Execution Optimization is an instruction file that shapes how a model runs a task: six stages that repeat, with the last one looping back to fixes until the tests pass.
01Understand
Pin down the task
The goal, what success looks like, and the constraints - before a single line of code.
02Explore
Map the project
Files, structure and the tools on hand. No guessing how the project works.
03Decide
Choose the path
Search, reuse an existing solution, or build from scratch. The heart of the method.
04Split
Break up the work
Small stages, each with a result you can check on its own.
05Test
Verify every stage
Nothing gets built on top of a stage until that stage passes.
06Fix & loop
Fix from evidence
Fixes come from test results, not guesses - and the loop runs until it passes.
SearchWhen to searchWhen the answer may have changed, or isn’t in the project.
ReuseWhen to reuseWhen a library or existing code already solves it.
BuildWhen to buildWhen the solution has to be tailored - then built in stages.
04 / See it in actionClaude vs Argon · the video
Watch Argon
run with AEO.
Not a slide deck - a real build. Press play to see the method at work, then join the webinar to take it apart step by step.
Claude vs Argon - the videoPress play · sound on
One of the results: a full game built by Gemini 4 Argon following AEO.
05 / Inside the sessionOne live online session · hands-on, not theory
A real project, built live.
01
The problem, live
We run Argon on a real project with no guidance and watch exactly where it falls into the Execution Strategy Gap.
02
Inside the AEO file
We open the file section by section: how it steers exploration, decisions, splitting the work and testing.
03
Before vs after
Same project, same task. We compare the unguided run, the guided run, and Opus 5.5 side by side.
06 / Straight talk
Not “it’s better.”
Not “it’s better.”
Test it yourself.
What you’ll see are results on specific tasks we ran - not a final verdict on which model wins. That’s why the file is yours after the session: apply it to your own work and judge by your own numbers.
1Get the file2Apply it to your project3Measure the difference
07 / Your hostMecha AI · Mecha ML
Eng. Amr Tweg
Founder, Mecha ML · Lead Scientist & Co-Founder, Mecha AIBuilds and experiments with AI products and intelligent systems. His approach: start with a clear question, build something testable, and let the results decide the next step.
Mecha has collaborated with
08 / Questions
Before you register.
Straight answers to what people ask most. Anything else, ask us on WhatsApp.
Ask on WhatsAppIs the webinar free?
Yes. Registering and attending are free. Leave your details and our team sends you the session link and time on WhatsApp.
Do I need to be a developer?
It helps if you already use AI models on real work. We apply the method to a coding project live, but the core idea - guiding how a model runs a task - is useful to anyone working with agents.
When do I get the AEO file?
The file is for registrants. It reaches you after the session so you can apply it to your own work and measure the difference yourself.
Does this mean Argon beats Claude?
No. The point is that how you run a model matters a lot - enough that a guided Argon gets close to Opus on the tasks we tested. Any general verdict on which model is better needs broader measurement, and we will be upfront about that.
Do I need a Gemini or Claude subscription?
Not to attend and follow along. To apply the method yourself afterwards, you will need access to the model you want to test.
Will the session be recorded?
We will confirm this with registrants before the date. Joining live is the best way to ask questions and watch the comparison as it happens.
Thu, Oct 29 · Online
Save your seat.
Save your seat.
The file’s on us.
One minute and you’re on the list. The webinar link and time arrive on WhatsApp, and the AEO file follows after the session.
- 01Free to attend
- 02Session link sent on WhatsApp
- 03The AEO file for every registrant
You’re on the list.
We’ll send the webinar link and time on WhatsApp before October 29, and the AEO file after the session. Want it faster? Message us now.
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