Bigg Mark

[Bigg Mark @bigg_mark72609]

@VERITY_HQ Those ones with beards
Fear them
They are weapons of destruction

[Stanlee | Web developer @stanlee0nX]

If I wanted to learn a new programming language in a considerate amount of time, here’s what I’d do.

I go to ChatGPT n prompt this;

I want to learn [LANGUAGE/TECHNOLOGY] in [TIME PERIOD].

You’re a senior software engineer, instructor, and curriculum designer with years of industry experience.

I can dedicate [X HOURS] per day.

Create a complete learning roadmap from beginner to job-ready level.

For each lesson:

- Explain concepts using simple notes.
- Provide practical examples.
- Give exercises to test understanding.
- Include mini projects and larger projects.
- Recommend relevant YouTube videos and documentation.
- Include common mistakes beginners make.
- Give quizzes and challenges before moving to the next topic.

Teach me using the 80/20 principle, focusing on the concepts most used in real world development.

Do not skip fundamentals.

Assume I already know [OTHER LANGUAGES OR SKILLS] and compare similarities and differences where helpful.

Create a weekly study plan and estimate how long each topic should take.

At the end of each lesson, provide:

- A summary.
- Exercises.
- A project.
- Interview style questions.

Do not overwhelm me with information. Teach one lesson at a time and wait for me to complete the exercises before continuing.

Teach me the way professional developers use this technology in production, not just how tutorials teach it.

(For developers specifically)

Reshare🙏🏾

[Suraj Sharma @suraj_sharma14]

If I had 6 months to become an Agentic AI Engineer.

I'd do this.

Stage 1: Python + Async Foundations
asyncio, FastAPI, event-driven architecture, error handling, API integration patterns.

Stage 2: LLM Fundamentals for Agents
Context management, model routing, token economics, latency tradeoffs, failure modes.

Stage 3: Tool Calling + Structured Outputs
Pydantic validation, function calling schemas, error recovery, dynamic tool discovery.

Stage 4: Memory + State Management
Short-term buffers, long-term vector recall, context compression, cross-session sync.

Stage 5: Single Agent Workflows
ReAct loops, plan-and-execute, self-reflection, iteration limits, graceful degradation.

Stage 6: Multi-Agent Orchestration
LangGraph/CrewAI, supervisor patterns, message passing, conflict resolution, handoffs.

Stage 7: Human-in-the-Loop Systems
Uncertainty detection, approval gates, audit trails, resume logic, intervention points.

Stage 8: Evaluation + Quality Assurance
Automated eval harnesses, LLM-as-a-judge, regression testing, hallucination metrics.

Stage 9: Observability + Tracing
Distributed tracing (LangSmith/Arize), cost dashboards, latency monitoring, alerting.

Stage 10: Security + Guardrails
Prompt injection defense, output filtering, PII redaction, sandboxed execution, compliance.

Stage 11: Production Deployment
vLLM/SGLang, Kubernetes scaling, CI/CD for agents, canary releases, rollback strategies.

Stage 12: Open Source + Portfolio
Ship autonomous agents publicly, write architecture docs, record demos, contribute to libs.

Most people stay stuck watching tutorials.

Builders get hired.

(Bookmark it)

[Himanshu Kumar @codewithimanshu]

I'm quitting my job to go full-in on Claude.

Just Asked it to:

Analyze mispriced Polymarket markets for arbitrage opportunities and find wallets using it to copy.

Turned $2K into $12K overnight.
Monitored 1,000+ wallets.

I realized something fast.

There are arbitrage bots I can't beat without code knowledge.

But I can find them. And copy them.

Claude built a monitoring terminal and connected it to a Telegram copytrading bot.

It's not a script. Not even a bot.

It's an AI agent that improves with every wallet it finds.

Fetches wallet behavior. How it trades. Arbitrage patterns. Position sizing. Timing.

70% win rate.
7 wallets copytrading right now from 500+ monitored.

Bot never pauses. Never gambles. Just math and profit.

You only need: Claude + a device + 1 hour per day.

Giving this free for 24 hours.

To get it:

1. Comment "cash"
2. Like and retweet this
3. Follow me @codewithimanshu so I can DM you

[Hridoy Reh @hridoyreh]

75 places to get backlinks for startup:

1. Chrome Web Store (DR 99)
2. Forbes (DR 94)
3. GitHub Pages (DR 97)
4. TrustRadius (DR 84)
5. AlternativeTo (DR 79)
6. SourceForge (DR 92)
7. Gumroad (DR 92)
8. Substack (DR 93)
9. Indie Page (DR 67)
10. Privacy Tools (DR 79)
11. OSS Gallery (DR 29)
12. Yelp (DR 94)
13. Alternative Me (DR 74)
14. SaaSHub (DR 78)
15. HubPages (DR 87)
16. YourStory (DR 85)
17. Medium (DR 94)
18. TrustMRR (DR 66)
19. Crunchbase (DR 99)
20. SEO Wins (DR 27)
21. GitHub (DR 97)
22. Imgur (DR 99)
23. Pinterest (DR 96)
24. Flickr (DR 94)
25. Pixabay (DR 92)
26. Pexels (DR 92)
27. Reddit (DR 95)
28. Quora (DR 92)
29. Goodreads (DR 92)
30. Tiny Startups (DR 50)
31. Hackernoon (DR 87)
32. TinyLaunch (DR 71)
33. Hacker News (DR 91)
34. Foundr (DR 76)
35. The Hustle (DR 79)
36. GrowthMentor (DR 72)
37. DZone (DR 84)
38. Smashing Magazine (DR 90)
39. Product Hunt (DR 91)
40. BetaList (DR 75)
41. MakerPad (DR 67)
42. StackShare (DR 79)
43. PeerSpot (DR 73)
44. Toolify AI (DR 73)
45. WIP (DR 55)
46. Vocal Media (DR 82)
47. TechCrunch (DR 92)
48. VentureBeat (DR 90)
49. Starter Story (DR 85)
50. Niche Pursuits (DR 73)
51. Founder Reports (DR 57)
52. Milestones (DR 26)
53. Boring Cash Cow (DR 26)
54. Micro Founder (DR 36)
55. Failory (DR 74)
56. Revenue Memo (DR 37)
57. Latka (DR 72)
58. Builder Society (DR 39)
59. Indie Niche (DR 93)
60. Indie Hackers (DR 80)
61. Fandom (DR 92)
62. Hashnode (DR 83)
63. Mixergy (DR 75)
64. First Round Review (DR 81)
65. Blogger (DR 94)
66. AppSumo Blog (DR 83)
67. WikiHow (DR 91)
68. DevTo (DR 90)
69. SaaStr (DR 77)
70. FounderPass (DR 52)
71. Entrepreneur (DR 91)
72. Indie Bites (DR 34)
73. SaaS Club (DR 59)
74. My First Million (DR 62)
75. Wikipedia (DR 97)

[SPEKULATOR @__spekulator__]

7 links i would save for a crypto trading bot research stack:
1. https://t.co/SdAnBotnEv — ccxt
use: one interface for exchange data/trading APIs
edge: cross-exchange data layer for bots
2. https://t.co/o30EADeAnS — Hummingbot
use: market making / connector framework
edge: market-making research stack
3. https://t.co/fsayZhalof — ccxt manual
use: exchange API patterns and order examples
edge: execution docs before bot code
4. https://t.co/xzslq03QiJ — vectorbt
use: fast strategy research/backtesting in Python
edge: test the idea before touching real capital
5. https://t.co/lsVvNyinDC — GitHub topic: trading-bot
use: scan bot frameworks and strategy examples
edge: idea discovery, not copy-paste alpha
6. https://t.co/ZDEbr2DxY0 — Freqtrade
use: open-source crypto trading bot framework
edge: strategy testing and bot ops baseline
7. https://t.co/aCDl5f1eAH — GitHub topic: crypto-bot
use: find crypto automation repos
edge: source map for bot builders
the point is not to copy a bot.
the point is to build a research loop: data → test → execute small → log every mistake.
not financial advice.

[Bigg Mark @bigg_mark72609]

@VERITY_HQ That's their purpose on this earth

[Bigg Mark @bigg_mark72609]

@UGSPECIAL All this your rubbish talk because say your bricklayer dey charge you extra... Tueh I pour you spit

[Bigg Mark @bigg_mark72609]

@StatiQfit Lord Future of the Uchiha clan

[bl888m @bl888m]

my friend got fired from Goldman quant desk last December

he was making $340K/year analyzing prediction market trading patterns

instead of applying to another bank - he deployed his entire model on Kreo

$600 → $89,400 in 4 weeks

total cost: $0

he said: "the edge I built for Goldman works better here, because on Wall Street you compete against other quants. On Polymarket you compete against people who trade based on feelings"

he deployed 4-pattern automation system in one night

same logic Goldman ran on client portfolios:

Deep Wallet Analysis: scan 14,000 Polymarket wallets, filter top 2% by category - auto-copy only their dominant edge

Priority Mode: when profitable traders enter, mirror within 0-2 seconds - manual = 12 second delay = profit gone

Weather arbitrage: NOAA updates 18 minutes before Polymarket - bot catches window automatically

Custom rules: max 8% per position, auto-cut -11%, Kelly sizing - 10 concurrent max

all 4 run simultaneously

portfolio optimizer auto-balances

fractional Kelly, max 8% per trade, 10 positions live

Goldman's model returned 17% last year on client money

his system returned 14,800% in 4 weeks on $600

his boss called asking him to consult

he said he's busy trading

start tonight: deposit $50, enable 4 patterns: https://t.co/74ONUwvcKq

first auto-copies execute within 24-48 hours

doesn't need consulting fees anymore

[Livsun @L1vsun]

a citadel quant told me something that broke my entire trading framework

"we don't predict markets. we model the state machine"

he explained markov chains in 90 seconds

the market is never random - it always exists in one of three states

trending up, trending down, ranging - each has a fixed probability of shifting to another

build the transition matrix from real price data:

> trending up -> 68% stays trending, 21% flips to range, 11% reverses
> ranging -> 54% stays range, 28% breaks up, 18% breaks down
> trending down -> 61% stays falling, 24% flips to range, 15% reverses

now you're not guessing, you're playing probability

identify current state, enter with the 68% edge, size with kelly criterion based on that probability

the formula is public - markov published it in 1906

hedge funds use it, the math costs nothing

what costs you is asking the wrong question

"where is price going?" is random

"what state am I in right now?" has an answer

transition matrix built from 10 years of data is your edge

Bookmark it

not a signal, not an indicator - just conditional probability that compounds every single trade

[Livsun @L1vsun]

guy who took 4 AI trading courses is still at breakeven

24yo at jane street who built models made $680k last year

same tools, different question

retail uses AI to predict price. quants use it to model how fast everyone else is already predicting the same price

that second question is signal decay - it's basically all of quant AI in one concept

every edge has a half-life. AI isn't finding signals - it's timing their death

how crowded is this pattern right now? how fast is the edge decaying?

Renaissance ran 66% annual returns for decades. not better signals - better departure timing

retail optimizes entry. quants optimize the exit before saturation

math behind this is public - arxiv, hundreds of papers on alpha decay, all free

Bookmark this important knowledge

but nobody on trading twitter ever links you there

gap isn't intelligence - it's the question nobody told you to ask

[Bigg Mark @bigg_mark72609]

@TenmanNoble1 Guyyy deadly type shit

[Bigg Mark @bigg_mark72609]

@yabaleftonline Tueh I pour adeleke family spit

[Bigg Mark @bigg_mark72609]

@FridayyG4ML Samson wey trust woman wetin sup?
Abi even Adam the first man wey trust eve how e be for am?
Trust women at your own risk
Dey like who carry family inheritance dey play aviator

[Bigg Mark @bigg_mark72609]

@whoisayomide Your broke ass be making comments because you're not at the level. Tsk

[Bigg Mark @bigg_mark72609]

@BowesChay This goes to show a lot😂

[Bigg Mark @bigg_mark72609]

@Kvnza_SA Lol na that DNA una use play mexico abi do you guys exchange DNAs

[Bigg Mark @bigg_mark72609]

@flowzki Oga shut up

[Bigg Mark @bigg_mark72609]

@officialEFCC Eagle ke, abi na chekeleke una be
The most biased after inec is you guys