Background: Co-founder and CTO of Sixth AI, an AI coding agent VSCode extension I built from Lagos to 350k installs and $27k in monthly revenue, with users organically switching from GitHub Copilot. Architected the full backend including a client-side agentic layer with a pure LLM proxy backend that handles thousands of concurrent requests. Owned everything from infrastructure decisions to VSCode marketplace growth and distribution.
Looking for a founding engineer or early engineer role at an AI-native startup where I can bring more than just code, product thinking, distribution instincts, and the kind of context that only comes from having built and shipped something real under real constraints. That's the sweet spot for me but open to other serious engineering roles where this kind of background is valued.
Open to full-time remote roles or startups willing to sponsor relocation/visa processing.
Show the math.. only about 12% of buyers buy new cars. Economical, efficient EVs can be had for $20k. Renting a big truck occasionally can be as little as $20, but even at $5000 for a truck rental... most people are buying trucks that cost $10, $20, $30K more than an enconomy car.
You could alternatively just rent a car or truck when you need one, and not one a car at all?
if you arent affluent, all the costs that come with car ownership are a bit excessive.
even still you might want to go for the cheap EV, and just not do things that require a pickup, rather than paying the costs of the pickup all the time
> no one is willing to admit the EV tech isn't just there yet
The easy explanation is that it's because it is there. The article is about the rapid decline of companies that believe otherwise. They aren't doing to great.
A wealthy nation with a small population that has plenty of money to update their infrastructure is not comparable to upgrading the grid and converting the fleet of 250M cars in the US, which is a mess of 50 states who spend varying amounts of money on their infrastructure.
The US grid is already stressed by all these new data centers, where is the power to send 10kW of power minimum to tens to hundreds of millions of vehicles every day going to come from?
100M vehicles times 10kW divided by one million is One Million Megawatts.
One Thousand Gigawatts. That’s five hundred 2GW power plants. Four thousand solar panels make 1MW, four million solar panels make 1GW, four billion solar panels make 1000 GW.
And that’s 40% of the fleet converted to EVs, and does not account for diesel semi-tractors being converted to EV.
> A wealthy nation with a small population that has plenty of money to update their infrastructure is not comparable to upgrading the grid and converting the fleet of 250M cars in the US, which is a mess of 50 states who spend varying amounts of money on their infrastructure.
The US is plenty wealthy per capita, around the same or more than Norway. It has plenty of money to upgrade it's infrastructure, it just chooses to spend it on other goals such as bombing Iran.
This is not a particularly useful statistic when talking about the number of cars being bought.
Almost invariably, "per capita wealth" uses mean wealth. This is dramatically different from the median wealth.
When you've got a few individual people worth upwards of $200 billion, that means that each one of them adds roughly $1000 to the "per capita wealth" number, while only ever accounting for something like a dozen cars at the outside.
> which is a mess of 50 states who spend varying amounts of money on their infrastructure.
That is not a tech problem, which is the claim I was replying to.
I saw your deleted comment about four charging stations costing $200,000 or so. Four petrol stations also cost that much. Nobody is saying infrastructure is free, but phasing out infrastructure is simply a matter of time and political will, not a fundamental tech problem.
I agree that we’ll eventually fully convert to EVs, it’s just going to take way longer than a lot of people expect. It’s going to be tens or hundreds of billions of dollars to upgrade electrical transmission, distribution, and premises distribution.
Edit: You nailed it, it’s a political problem in the US.
> It’s going to be tens or hundreds of billions of dollars to upgrade electrical transmission, distribution, and premises distribution.
Would certainly happen a lot faster if, for example, America spent the $200 billion the Pentagon just asked for the Iran war on infrastructure instead. It would even benefit Americans, imagine that! America is the wealthiest country in the world by far, it has the capital to facilitate the process, but taxpayers would rather blow it on bombing schools across the world.
I agree, I’m just saying it’s easier for a country with a sovereign wealth fund and ridiculous oil royalties to handle upgrading their infra to handle EVs for 6M is much easier than doing it in the US which has extremely low average population density, 250M+ vehicles and 400M people, and a mess of separate but inter-tied grids and varying levels of infrastructure investment depending on which state you are in.
Do you feel that externalities should not be taxed? That individuals should be able to do things that collectively cost everyone else in society money, without any expectation that they pay money into a societal fund to address the problems created by their own actions?
from the impacts of the straight of hormuz closing, and the Russian invasion of Ukraine - electrification and removing dependence on oil and gas is a major defense cost.
any spending on EV adoption should be considered part of the NATO commitment
Per my calculations, EVs are cheaper over the whole vehicle lifetime. I included construction costs and usage costs, in terms of money, environmental impact, and health impacts.
Of course, no cars is even better. If we could all ski, cycle, or run, it would be even cheaper and better for our health. It’s a trade of.
That's a strange statement considering that 20% of new vehicles sold globally are EVs. And that's not just China propping up the numbers: 20% of new vehicles sold in the EU are EVs as well.
Obviously that's not "fully replace" territory, but that is most definitely a critical mass beyond being a niche vehicle category.
The EV market globally is growing much faster than the ICE market. At the rate of technology and pricing improvement, EVs taking over the majority of sales is almost inevitable.
It's just not growing as quickly in certain markets like the USA, and many predictions were too aggressive.
Who is really going to prefer ICE vehicles when we start seeing median MSRP vehicles start to reach customers with 400-500mile+ range numbers? This isn't some crazy idea (e.g., see the 2026 BMW i3, estimated range of 440 miles in an entry level premium sedan - in 5-10 years that's the kind of spec you'll be seeing in a cheap Kia).
There just isn't that much more progress in battery technology and pricing left to achieve to make ICE fully obsolete, and that is exacerbated by oil prices that are now set to rise for years to come.
In 2024[1]:
- 37.2% in Sweeden
- 51.6% in Denmark
- 30.4% in Finland
of newly registered cars were BEV. Only Norway reaches 89% you are talking about. The total average of newly registered BEV cars in European Union was 13.6%.
The EV tech is here,but the grid in most EU countries is certainly not. The proliferation of heat pumps in the local area caused 3 blackouts caused by a failure of a local transformer - something that hasn't happened before or at least not as frequently. And in most countries you are looking at doubling the electricity consumption if all road transport was to switch to electricity.
In 2025[1]: 64.3% in Sweden - 69.3% in Denmark - 55.2% in Finland. Across the EU 2.6 million BEVs were sold out of ~13 million cars in total, i.e. 20% in 2025. That's on top of 1.3 million PHEVs which is an even faster growing segment.
So it's not quite 80% yet, but it's getting there fast.
They just have to replace most use cases. There will come a point, not too far away, where battery progress makes them cheaper to purchase than petrol cars (for many use cases the point may already have come where TCO is lower, and Trump’s oil crisis will only speed the arrival of that point for more use cases.)
I have gone back to manual coding to remove this AI induced laziness because i discovered immediately the LLM starts making some useless engineering decisions it does it like it knows what it's doing and also very deceptive and sometimes it's just easier to do it by myself other than trying to get the AI to do it,LLMS get so confidently wrong.
And it sounds so knowledgeable and authoritative in its replies. And i like being told "great idea"...
OK, that is a joke i don't like it that much coming from a mindless agent.
But in the dialog it becomes so convincing that i struggle not to anthropomorphize it.
Remember "Her" with Joaquin Phoenix? i wont fall in love with it but i might entrust it with my root passwords?
I think group dynamics comes with a turn taking ambiguity. unlike in one-on-one dialogue that's structurally clean since there's a clear prompt, a clear response, and a clear feedback signal for RLHF.
Sure, messy to implement. But maybe that messiness is the fix. Clean 1-on-1 is exactly why AI learns to flatter — one voice, one signal, no pushback. Group is harder to train but harder to game
Isn't windsurf now antigravity? because i still used antigravity for a while this year because of how the agent can natively try to test web pages using chrome which helps it find UI bugs,but i use mostly claude code now though
This looks nice,would be really cool if this has a huge adoption in the future because i find SEO frustrating on github,does it have it's own custom SEO system for ranking repos?
The frustration that started this: I kept context-switching between Grafana dashboards, log files, and docs every time something broke in production. I wanted to just ask what was wrong and get an actual answer.
Argus is an open-source AI agent that monitors your infrastructure and investigates anomalies autonomously using a ReAct loop with 18+ tools, reading logs, querying metrics, tracing requests then proposes fixes for your approval before anything executes. The human-in-the-loop part was intentional; I didn't want an agent that could nuke a database without asking first.
It's LLM-agnostic (OpenAI, Anthropic, Gemini) and runs entirely in one Docker container. SQLite + DuckDB under the hood, no external dependencies.
Still early but already handles the case I built it for — would love brutal feedback, especially from anyone running their own infra.
I got tired of AI agents (Cursor, Claude Code) instantly writing hundreds of lines of bad code from a misunderstood prompt, burning tokens and time.
We built Overture: an open-source MCP server that intercepts the agent's plan and renders it as an interactive graph. You can review dependencies, inject context into specific nodes, and approve the flowchart before execution starts.
Would love any technical feedback or thoughts on the approach.
I'm a visual learner. Whenever I try to understand something hard like dynamic programming, vector calculus, how attention mechanisms work, reading about it only gets me so far. I need to see it move.
So I built Prism AI. When you ask it to explain something, it doesn't just return a report. If the topic calls for it, it generates an interactive visualization inline. Ask it to explain dynamic programming and you get a 2D animation with the code on one side and a decision tree on the other, recursively solving subproblems as a highlighter steps through each line. Ask it how a vector field works and it renders an interactive 3D field you can rotate and probe. Ask it how the attention mechanism in a transformer works and it shows you the actual weight matrix lighting up across tokens.
The research pipeline underneath is a Plan-and-Execute setup , a PlanningAgent breaks your query into a roadmap, then multiple Researcher Agents crawl sources in parallel via asyncio, with a LangGraph state machine handling retries when sources are weak. But the viz generation is honestly the part I care about most and the part I'm still iterating on hardest.
Feedback I'd value: 1. What complex topic would you most want explained this way? 2. Has anyone found a clean way to decide when an agent should generate a visual vs just write prose — that decision boundary is still the messiest part of my pipeline.
Remote: Yes, fully remote preferred. Open to relocation with visa sponsorship for the right opportunity, particularly EU/UK.
Willing to relocate: Yes, with visa support
Technologies: Python, FastAPI, Django, TypeScript, Node.js, Express.js, React, PostgreSQL, Redis, kubernetes, AWS, GCP
Linkedin: https://www.linkedin.com/in/precious-balogun-7392141b2/
Github: https://github.com/precious112
Email: [email protected]
Background: Co-founder and CTO of Sixth AI, an AI coding agent VSCode extension I built from Lagos to 350k installs and $27k in monthly revenue, with users organically switching from GitHub Copilot. Architected the full backend including a client-side agentic layer with a pure LLM proxy backend that handles thousands of concurrent requests. Owned everything from infrastructure decisions to VSCode marketplace growth and distribution.
Looking for a founding engineer or early engineer role at an AI-native startup where I can bring more than just code, product thinking, distribution instincts, and the kind of context that only comes from having built and shipped something real under real constraints. That's the sweet spot for me but open to other serious engineering roles where this kind of background is valued.
Open to full-time remote roles or startups willing to sponsor relocation/visa processing.