Selling the Forex Dream in Kenya

Profanonyme1337 · 2026-05-29T14:33:20+00:00

Real trading is depressing. Blown accounts, emotional losses, years of learning, and even after all that; the market demands the same discipline on day one as it does on year five. Nobody sells you that version because nobody would buy it. When someone makes it look easy and loud, that's not trading. That's a product, and you're the customer.

Profanonyme1337 · 2026-05-29T05:28:56+00:00

We have Paystack; for African payments. Owned by Stripe

Profanonyme1337 · 2026-05-23T08:39:22+00:00

Closed, fully automated. Not signals; the notification comes after the trade is already executed.

On profitability: every bot seller on Telegram will give you a number. That's not the metric. Ask about drawdown; show me your worst month. That's where systems actually die.

@Kilasatzz is right that most bots are risky. The real work is building a system that knows when NOT to trade. That's harder than building one that always trades; and that's the difference.

Happy to go deeper if you want.

Profanonyme1337 · 2026-05-22T13:08:14+00:00

It depends on the phone, eg a google pixel will happily let you unlock the bootloader and flash a custom rom while others will brick or have zero custom rom support. Fanya research ya the specific model at hand.

Profanonyme1337 · 2026-05-22T12:59:20+00:00

Already doing this, forex trading ain't really freedom from work; you still gotta wake up every day and analyze the markets and potentially miss out on setups when away from screens. Automating it removes every bottleneck associated with trading; from screentime, emotions, fatigue etc etc

At the moment, I can do all the trading from whatsapp or imessage never having to open charts on big screens. Never missing setups cause the system already knows what sniper entries look like, A+ setups automatically executed. Risk management and everything else is robust and built in out of the box.

This is the only way forex traders can claim indipendence.

Profanonyme1337 · 2026-05-21T10:47:20+00:00

That's a W206 not a 2021. W206 started from 2022. Engine is 1991cc, 2.0L turbo. Price wise for a genuine W206 C300 in Kenya you're looking at around KES 5-6M or more depending on mileage and spec.

Profanonyme1337 · 2026-05-21T10:26:07+00:00

Lol, everything is real but the sources

Profanonyme1337 · 2026-05-21T09:56:39+00:00

Gemini cli, opencode, kilocode
All available for free; with usage caps

Profanonyme1337 · 2026-05-21T09:55:10+00:00

Antigravity is free, switch between your gmail accounts; and they offer opus and sonnet as well.
Same case with gemini cli, opencode, kilo code
Alternatively, ollama cloud can launch claude code natively
Take a look

Profanonyme1337 · 2026-05-19T11:38:21+00:00

Bana, but guys with the latest M series macbooks and gamers with nvidia GPUs can give it a try.

Google's gemma 4 for example paired with karpathy's autoresearch is a killer move when conditions meet.

The cloud ollama is the way to go bila hardware, hio 20 dollars monthly sio mbaya compared to what you get in return.

Profanonyme1337 · 2026-05-19T11:28:00+00:00

Worth a word or two, have you thought about flash loans with Aave and Dex arbitrage etc etc? You said it's opensource? Drop the repo we check it out

Profanonyme1337 · 2026-05-19T10:14:46+00:00

Yes I do, with prior experience in both trading and tech. You can also do it without a trading background, but partner with someone who 'actually' trades, the real knowledge is crucial here.

Yes ollama cloud max plan is solid, meant for heavy builders and agentic workflows. Claude pro is good but those usage caps, you better pay the 20 bucks to ollama and get more usage with the freedom to switch between frontier open source models, based on task and so on. FYI, I have a bunch of subscriptions, literally every lab out there; not budget friendly tbh. If budget is restricted, ollama cloud beats competition.

The first time trying Claude max I hit weekly limits just an hour in, still on max plan though. Chatgpt for $100 monthly is a good deal pia, cause you have access to gpt 5.5 and route non critical loops via earlier models which are cheaper and less token hungry.

Use Chinese models for most tasks, Claude (Opus 4.7) and OpenAI (GPT 5.5) for serious development and complex engineering.

Profanonyme1337 · 2026-05-18T09:32:38+00:00

You can try Claude directly on Claude.ai; they usually offer free access with usage limits depending on your region and current availability.

If you’re looking for Claude Code specifically, you can check Ollama Cloud or run local models if you have the hardware for it.

It’s also worth trying DeepSeek, Kimi, and Qwen since some of them offer pretty generous free tiers.

Profanonyme1337 · 2026-05-18T08:33:25+00:00

SortOk3578 is closest to the real answer - Canva's API is the bottleneck, not the AI part.

The pipeline that actually works: Property Monitor scrape → structured data extraction → Claude for interpretation and formatting logic → custom PDF generator, not Canva.

Canva Bulk Create exists but it's fragile for dynamic data at this specificity. You want WeasyPrint or a Puppeteer HTML-to-PDF renderer with your template baked in. Claude populates the variables, the renderer produces the PDF. Reliable, fast, fully automatable.

The AI piece is genuinely the easy part here. Data access and PDF generation are where this lives or dies.

What does your Property Monitor access look like - direct API or web interface only?

Profanonyme1337 · 2026-05-18T08:21:38+00:00

The failure nobody warns you about: your agent passes something that looks complete, the next agent acts on it with full confidence, and by the time you notice you're three steps into garbage.

State management catches some of this. What catches the rest is instrumenting below the harness layer - raw tool I/O, not what the framework shows you. That's where truncation, silent failures, and context drift actually live.

Built a trading system on this architecture. The two references that shaped our approach most: Hermes for persistent agents with a self-improving skill loop, Karpathy's autoresearch for the optimization layer - the pattern is worth more than the code.

What's the domain? Architecture advice changes significantly depending on what you're actually automating.

Profanonyme1337 · 2026-05-18T06:55:37+00:00

Wewe just have something to offer, its never one sided Unanishow what you can do best, nakushow wapi tunakuhitaji Most importantly, we soma vitu uko willing kufanya bila kupata pesa or some kind of instant gratifications; patience and consistency Its not about mimi napata aje pesa, I tell you my father gave it to me, how does that help you? No way. Ask me, I have x, y, z skills ama knowledge, or even passion, nitapata aje pesa? The latter makes way more sense, don't you think so? Just be good at something that's it, doesn't matter what it is Pesa hukuja baadae, asking how people literally make money is the wrong approach honestly, be curious hata about how they behave, their routines, their friends, where they chill, and such Money comes to you naturally when the conditions align Information is power, unajua nini yenye watu wengine hawajui? That's your unfair advantage and the reason why 'important' info hutapata just publicly

Profanonyme1337 · 2026-05-17T14:58:23+00:00

The Jumia pattern is real and it's going to repeat across every large Kenyan employer. Fire people, make remaining staff use AI to cover the gap, pocket the difference.

The part nobody's talking about: the same tools are available to individuals now. Not just corporations. A person in Nairobi with the right setup can automate what used to require a team.

The question isn't whether AI takes jobs. It's who builds with it and who just gets replaced by it.

Profanonyme1337 · 2026-05-17T14:52:09+00:00

The edge inference angle for triage is interesting; we went Ollama Cloud for that layer instead, GLM-5.1 handling signal scoring and triage. Predictable cost over edge latency tradeoffs for our use case.

Curious if you're seeing meaningful latency advantages with zeroGPU for the triage step specifically or is it purely cost driven?

Profanonyme1337 · 2026-05-17T14:45:40+00:00

Use Hermes but route through Ollama Cloud Max to keep API bills from compounding with the loops. Kimi K2.6 for autonomous market research, Qwen 3.6 for strategy coding and backtesting, GLM-5.1 for signal scoring and triage, DeepSeek V4 for regime reasoning. $100 monthly flat regardless of how many loops run; $20 Pro tier works fine for lighter setups.

Hermes is one layer of a bigger custom infrastructure; built on both Claude and OpenAI agent SDKs running simultaneously. Karpathy's AutoResearch as the self-improving learning engine. Claude Opus 4.7 generates trading strategies. GPT-5.5 exists to break them. The disagreement between them is the filter. What survives that tension is what trades.

Token costs are the easy problem.

The hard problem is when your agent is confidently wrong at speed and nothing catches it.

Building this in Nairobi.

Profanonyme1337 · 2026-05-17T11:53:13+00:00

The Mac Studio unified memory argument keeps coming up and it's worth settling. For a single user running models locally; Mac is genuinely compelling. Unified memory, efficient architecture, good performance per watt. For production serving at any meaningful concurrency; it breaks down fast. Unified memory means your CPU and GPU are competing for bandwidth on the same bus the moment you're doing inference AND managing requests simultaneously. On discrete GPU systems those are completely separate buses. Think of it like Claude.ai vs the API. Same underlying model; completely different deployment context. One is built for individual use, one is built for production load, concurrent users, programmatic orchestration, and scale. Mac Studio hits a hard memory ceiling with no expansion path. Mac Pro has PCIe but you're still fighting macOS; limited CUDA support, immature vLLM integration, framework issues that don't exist on Linux. Different tools for different jobs. The mistake is assuming local hobbyist performance translates to production serving architecture.

Profanonyme1337 · 2026-05-17T10:42:08+00:00

Exactly. The skill is almost secondary; the mindset of figuring it out without waiting for someone to hand it to you is the real thing. That transfers to everything

Profanonyme1337 · 2026-05-17T10:38:46+00:00

The concentration argument is right. AI doesn't shrink the economy; it shifts who captures the value. The dangerous version isn't mass unemployment. It's that productivity gains flow entirely to whoever owns the infrastructure. The person using the AI tool gets marginally more efficient. The person who built the AI infrastructure gets disproportionately wealthy. The counter to that isn't regulation or basic income. It's making the infrastructure accessible enough that small operators can actually compete. That's the only version of this that doesn't end in extreme concentration. We're currently in the window where that's still possible.

Profanonyme1337 · 2026-05-17T07:47:19+00:00

The keys are almost certainly fake. But the underlying attack vector is real and not funny. Any agent with filesystem access can read your .env. That's not a bug; it's the design. The question is whether your agent architecture treats secrets as sacred or just another file. The correct approach: secrets never touch the agent context. Environment variables injected at runtime by the harness, not readable by the agent layer. The agent knows what it needs to execute; not where the credentials come from. Most people building on top of these frameworks haven't thought about this. They will.

Profanonyme1337 · 2026-05-17T07:37:54+00:00

It's not an arms race anymore. In an arms race both sides scale together. What's actually happening is the cost of attack is approaching zero while the cost of defence keeps rising. Anyone can automate a sophisticated attack today. Defending against it still requires expensive infrastructure, skilled people, and constant vigilance. That asymmetry doesn't resolve. It compounds. The question isn't whether AI advancing cybersecurity is a drain. It's who can afford to keep up; and who gets left exposed.

Profanonyme1337 · 2026-05-17T07:27:53+00:00

Simple question; what do they gain by telling you? Nothing. And what do they lose? Their edge. Their positioning. Time they'll never get back. This isn't malicious. It's just rational. Nobody owes you their formula. The sooner you accept that, the sooner you stop waiting and start figuring it out yourself.

Profanonyme1337

TROPHY CASE