In Rust We Trust 🦀 - rust

Rust Memory Layout Under the Hood

Nikolai Shelekhov — Wed, 25 Feb 2026 00:00:00 +0000

</p>

Every Rust struct you write is a memory layout decision.</p>

The kind of thing I wish I had a clear reference for when I was staring at perf output wondering why my “simple” struct was blowing cache lines. So I made one.</p>

Most engineers never think about it. But the compiler does.</p>

Building an AI Coach That Sees Your Factorio Factory

Nikolai Shelekhov — Sun, 15 Feb 2026 00:00:00 +0000

</p>

I got tired of alt-tabbing to ask Claude about my Factorio factory.</p>

Every time I wanted advice, I had to describe my setup manually. “I have 4 furnaces, 2 steam engines, researching automation…” — and half the time I’d forget something important or get the numbers wrong.</p>

So I built a tool that lets Claude see the game directly.</p>

Factorio as an AI Benchmark

Nikolai Shelekhov — Tue, 10 Feb 2026 00:00:00 +0000

The best AI models today can barely automate early-game smelting in Factorio.</p>

Meanwhile, experienced human players build megabases processing millions of items per minute — with perfectly ratioed production lines, optimized train networks, and nuclear power grids running at scale.</p>

That gap is interesting.</p>

Why Factorio Is Hard for AI</h2>
Factorio is not just a game. It is a real-time systems optimization problem.</p>
It requires:</p>

Long-horizon planning</li>
Resource dependency tracking</li>
Spatial reasoning</li>
Throughput optimization</li>
Incremental refactoring of live systems</li> </ul>
The game punishes short-term thinking.
Every early design decision propagates downstream.</p>
This makes it fundamentally different from most existing AI benchmarks, which are:</p>

Static</li>
Text-only</li>
Short-horizon</li>
Deterministic</li> </ul>
Factorio is dynamic, persistent, and adversarial to naive planning.</p>
The Factorio Learning Environment</h2>
There is already an open-source research effort exploring this space:</p>
Factorio Learning Environment
Published at NeurIPS 2025.</p>
It exposes a live Factorio server to LLM agents.
Agents write Python code to interact with the environment and attempt to build automated factories.</p>
The results so far highlight how difficult the problem really is.</p>
Even strong language models struggle with:</p>

Maintaining state over long sessions</li>
Correctly sequencing multi-step production chains</li>
Recovering from partial failures</li>
Designing scalable layouts</li> </ul>
This is not a prompt engineering problem.
It is a systems reasoning problem.</p>
Why This Is an Interesting Benchmark</h2>
Factorio introduces properties that resemble real-world infrastructure engineering:</p>

Graph-based dependency trees</li>
Constrained resource allocation</li>
Throughput bottlenecks</li>
Distributed logistics (trains, belts, bots)</li>
Continuous optimization under growth</li> </ul>
It is closer to distributed systems design than to puzzle solving.</p>
That makes it a compelling unsaturated benchmark for autonomous agents.</p>
A Rust-Based Approach</h2>
I’m currently experimenting with a Rust rewrite of the agent layer using Rig.</p>
The direction is deliberate.</p>
1. Typed Tools</h3>
Every game action becomes a strongly typed tool:</p>

Place entity</li>
Connect belts</li>
Query inventory</li>
Inspect recipes</li>
Read map state</li> </ul>
The domain is highly structured.
Rust’s type system allows encoding that structure directly into the interface.</p>
2. Multi-Turn Agent Loops over RCON</h3>
Instead of single-shot execution, the agent operates in iterative loops:</p>

Observe world state</li>
Plan next action</li>
Execute via RCON</li>
Re-evaluate</li> </ul>
This creates a feedback-driven control system rather than a stateless command generator.</p>
3. RAG over the Recipe Graph</h3>
Factorio’s crafting tree is a dependency graph.</p>
Using retrieval over:</p>

The recipe tree</li>
Wiki documentation</li>
Item production chains</li> </ul>
allows grounding decisions in structured domain knowledge instead of relying purely on model memory.</p>
Why Rust Fits</h2>
Factorio is deterministic and rule-based.</p>
The action space is structured. The state transitions are explicit. The constraints are mechanical.</p>
Rust feels like a natural fit for:</p>

Modeling state transitions</li>
Enforcing invariants</li>
Building typed agent tooling</li>
Keeping orchestration predictable</li> </ul>
When the domain itself is a graph of dependencies, types become leverage.</p>
The Gap</h2>
Humans build megabases.</p>
AI struggles to build a stable smelting line.</p>
That gap is not just amusing — it’s informative.</p>
It exposes the limits of current reasoning systems when faced with:</p>

Long-horizon planning</li>
Structural optimization</li>
Persistent world interaction</li> </ul>
Factorio may quietly become one of the most revealing AI benchmarks available.</p>
The factory must grow — for both humans and AI.</p>

How I Keep Up With Tech Trends

Nikolai Shelekhov — Thu, 15 Jan 2026 00:00:00 +0000

“How do you follow all the tech news and programming trends?”</p>

I sometimes get this question in interviews.</p>

My answer is simple:</p>

RSS.</p>

Yes — that “dead” technology from the 2000s.</p>

Why RSS Still Wins</h2>
Modern content consumption is algorithm-driven:</p>

Infinite scroll</li>
Engagement optimization</li>
Notification loops</li>
Recommended content you didn’t ask for</li> </ul>
The result is noise.</p>
RSS flips the model.</p>
You choose the sources. You get the updates. Nothing else.</p>
No ads. No ranking algorithms. No engagement tricks.</p>
Just a chronological stream of content you explicitly subscribed to.</p>
What Most People Don’t Realize</h2>
Most technical platforms still publish RSS feeds:</p>

Tech blogs</li>
Documentation sites</li>
Security advisories</li>
GitHub releases</li>
YouTube channels</li>
Reddit communities</li>
Mastodon accounts</li> </ul>
RSS never died. It just stopped being marketed.</p>
My Setup</h2>
I use News Explorer</strong> as my primary reader.</p>
It supports:</p>

RSS feeds</li>
YouTube</li>
Reddit</li>
Mastodon</li>
Bluesky</li>
Podcasts</li> </ul>
Everything syncs via iCloud across devices.</p>
No external accounts. No cloud dashboards. No algorithmic layer.</p>
Just folders and feeds.</p>
Scale</h2>
I currently track 6,000+ articles across:</p>

Rust</li>
Polkadot</li>
Solana</li>
Security advisories</li>
Systems programming blogs</li>
General software engineering</li> </ul>
All organized. All searchable. All in one place.</p>
It replaces:</p>

Dozens of open tabs</li>
Social media scrolling</li>
Random bookmarking</li>
“I’ll read this later” lists</li> </ul>
The Real Advantage</h2>
RSS creates a pull-based information system.</p>
You are not fed content. You poll your sources.</p>
This small inversion has large consequences:</p>

No FOMO</li>
No engagement pressure</li>
No missing updates because an algorithm deprioritized them</li>
No context switching into unrelated content</li> </ul>
It is closer to how engineers think:</p>
Deterministic input. Controlled sources. Minimal noise.</p>
When It Makes Sense</h2>
RSS works best if:</p>

You care about specific ecosystems</li>
You follow technical releases closely</li>
You want signal over volume</li>
You value focus over discovery</li> </ul>
It is not optimized for entertainment.</p>
It is optimized for clarity.</p>
Final Thought</h2>
If you feel like you are drowning in tabs, or missing important updates because a feed decided they were “low engagement,”</p>
try RSS.</p>
Sometimes the most boring technology is the most effective one.</p>

Designing an On-Chain Price Oracle in Substrate

Nikolai Shelekhov — Sun, 09 Nov 2025 00:00:00 +0000

Accurate price data is foundational to any DeFi system.</p>
DEXs, lending protocols, liquidations, MEV strategies —
all depend on reliable and timely asset pricing.</p>
Instead of relying purely on external infrastructure, I wanted to explore a runtime-native approach using Substrate.</p>
The Goal</h2>
Design a modular price oracle pallet that:</p>

Fetches asset prices from external sources</li>
Aggregates them deterministically</li>
Stores them on-chain</li>
Exposes them to other runtime modules</li> </ul>
The constraint: maintain composability and determinism at the runtime level.</p>
Architecture Overview</h2>
The design uses Substrate’s off-chain workers:</p>

Off-chain worker fetches external price data</li>
Data is validated and formatted</li>
An unsigned transaction submits updated price information</li>
Runtime storage is updated</li> </ol>
This keeps:</p>

Network requests off the runtime path</li>
Deterministic execution within the state machine</li>
Minimal trust assumptions beyond data sources</li> </ul>
Key Design Decisions</h2>
1. Off-Chain Workers</h3>
External HTTP requests cannot block runtime execution.</p>
Off-chain workers allow background fetching without compromising block production.</p>
2. Fixed-Point Arithmetic</h3>
Floating-point operations are not deterministic across architectures.</p>
All price calculations use fixed-point arithmetic to ensure:</p>

Deterministic execution</li>
Predictable rounding</li>
Cross-node consistency</li> </ul>
3. Storage Layout</h3>
Prices are stored in optimized maps keyed by asset identifiers.</p>
Design priorities:</p>

Fast reads (price access is frequent)</li>
Minimal storage overhead</li>
Clear upgrade path</li> </ul>
Why Not Just Use an External Oracle?</h2>
External oracle networks are powerful — but they introduce:</p>

Latency</li>
Trust layers</li>
Dependency on third-party infrastructure</li> </ul>
Embedding oracle logic inside the runtime:</p>

Improves composability</li>
Reduces architectural complexity</li>
Enables tighter integration with DeFi pallets</li> </ul>
For experimentation and MEV research, this approach gives full control over the data lifecycle.</p>
What I Learned</h2>
Building runtime logic reinforces an important principle:</p>
Blockchain development is systems programming.</p>
You’re writing deterministic state machines, with strict performance constraints, and zero room for undefined behavior.</p>
Rust and Substrate make that not only possible — but enjoyable.</p>

Why Rust is My Go-To for Systems Programming

Nikolai Shelekhov — Mon, 20 Oct 2025 00:00:00 +0000

After 8+ years of software engineering and 5 years specializing in systems programming, I’ve worked extensively with C, C++, Go, and Rust. Here’s why Rust has become my default choice for anything performance-critical.</p>

Blockchain or Rust? Why I Choose Both — On My Terms

Nikolai Shelekhov — Sun, 12 Oct 2025 00:00:00 +0000

A few months ago, I was asked in an interview:</p>
“What do you love more — Rust or blockchain?”</p>
My answer was immediate.</p>
Rust comes first.</p>
But not just any Rust work — deep, idiomatic, systems-level Rust programming.</p>
Rust First</h2>
What draws me to Rust is not hype.</p>
It’s:</p>

Memory safety without garbage collection</li>
Zero-cost abstractions</li>
Explicit control over performance</li>
Deterministic behavior</li>
Strong type-driven design</li> </ul>
Rust feels like systems programming done correctly.</p>
That foundation matters more to me than the domain.</p>
Blockchain — But Only at the Right Layer</h2>
If I work in blockchain, it has to be infrastructure.</p>
Not smart contracts. Not application-layer glue code. Not framework-heavy abstraction stacks.</p>
There is a fundamental difference between:</p>

Building on top of someone else’s platform</li>
Building the platform itself</li> </ul>
I’m interested in the second.</p>
Why Polkadot</h2>
Polkadot stands out for one specific reason:</p>
It is pure Rust.</p>
Substrate is not a thin wrapper around another runtime. It is not macro-driven sugar hiding complexity. It exposes the machinery.</p>
You write runtime logic. You design state transitions. You control storage. You reason about determinism.</p>
It feels like systems engineering — not scripting on-chain.</p>
That alignment matters.</p>
Infrastructure Over Applications</h2>
I am drawn to:</p>

Runtime design</li>
Consensus-adjacent components</li>
Performance-critical infrastructure</li>
Cross-chain execution logic</li>
State machine design</li> </ul>
Not UI. Not token launches. Not yield optimizers.</p>
I want to work on the systems that make everything else possible.</p>
The Boundary I’ve Drawn</h2>
My focus is clear:</p>

Deep systems programming in Rust</li>
Blockchain infrastructure (not application layer)</li>
Preferably within the Polkadot ecosystem</li> </ul>
That doesn’t invalidate other paths.</p>
It just reflects what I value.</p>
Why This Matters</h2>
Careers compound.</p>
If you spend years writing surface-level abstractions, you become good at surface-level abstractions.</p>
If you spend years designing deterministic state machines, optimizing performance, and reasoning about low-level invariants,</p>
you become something else entirely.</p>
I choose the latter.</p>
Rust is the constant. Blockchain is optional — but only when it allows Rust to be used at its full depth.</p>
That’s the line I’ve drawn.</p>

Async Rust Patterns I Use Every Day

Nikolai Shelekhov — Sun, 28 Sep 2025 00:00:00 +0000

Working on high-throughput backend services, I’ve developed a set of async patterns that help me write reliable, performant code. Here are the ones I reach for most often.</p>

In Rust We Trust 🦀 - rust

Rust Memory Layout Under the Hood

Building an AI Coach That Sees Your Factorio Factory

Factorio as an AI Benchmark

A Rust-Based Approach</h2> I’m currently experimenting with a Rust rewrite of the agent layer using Rig.</p> The direction is deliberate.</p>

How I Keep Up With Tech Trends

Final Thought</h2> If you feel like you are drowning in tabs, or missing important updates because a feed decided they were “low engagement,”</p> try RSS.</p> Sometimes the most boring technology is the most effective one.</p>

Designing an On-Chain Price Oracle in Substrate

Key Design Decisions</h2>

1. Off-Chain Workers</h3> External HTTP requests cannot block runtime execution.</p> Off-chain workers allow background fetching without compromising block production.</p>

Why Rust is My Go-To for Systems Programming

Blockchain or Rust? Why I Choose Both — On My Terms

Async Rust Patterns I Use Every Day

A Rust-Based Approach</h2>
I’m currently experimenting with a Rust rewrite of the agent layer using Rig.</p>
The direction is deliberate.</p>

Final Thought</h2>
If you feel like you are drowning in tabs, or missing important updates because a feed decided they were “low engagement,”</p>
try RSS.</p>
Sometimes the most boring technology is the most effective one.</p>

1. Off-Chain Workers</h3>
External HTTP requests cannot block runtime execution.</p>
Off-chain workers allow background fetching without compromising block production.</p>