DEV Community: Lucas Gragg

Auto-generate thread content with Groq

Lucas Gragg — Mon, 04 May 2026 14:09:07 +0000

Packaged social media scheduler this week after running it in production for ~60 days. Notes on what worked and what didn't.

The problem

Schedule and auto-publish posts across Twitter, Reddit, and other platforms from a single dashboard. Grow your audience on autopilot with queue management, optimal timing, and content recycling.

What's in the box

Multi-platform posting (Twitter, Reddit, LinkedIn)
Visual content calendar and queue management
Optimal posting time suggestions based on engagement
Content recycling and evergreen post rotation
Analytics dashboard with engagement tracking

Code sample

# Basic structure
class Bot:
    def __init__(self, config):
        self.config = config

    def run(self):
        while True:
            self.scan()
            self.execute()

If you want the full working version with all the battle-tested edge cases
handled, I packaged it here: Social Media Scheduler

Happy to answer questions about the architecture in the comments.

Building an Amazon price tracker (no API needed)

Lucas Gragg — Sun, 03 May 2026 14:08:59 +0000

Packaged amazon price tracker this week after running it in production for ~60 days. Notes on what worked and what didn't.

The problem

Track prices on Amazon products and get notified the instant they drop below your target. Supports wishlists, price history charts, and daily digest emails so you never overpay again.

What's in the box

Real-time Amazon price monitoring
Custom price drop alerts via email and Telegram
Price history charts and trend analysis
Wishlist import and bulk product tracking
Daily digest with biggest price drops

Code sample

# Basic structure
class Bot:
    def __init__(self, config):
        self.config = config

    def run(self):
        while True:
            self.scan()
            self.execute()

If you want the full working version with all the battle-tested edge cases
handled, I packaged it here: Amazon Price Tracker

Happy to answer questions about the architecture in the comments.

My 8-bot autonomous trading fleet (open source components)

Lucas Gragg — Sat, 02 May 2026 14:08:48 +0000

Packaged complete trading bot suite (all bots + agent + dashboard) this week after running it in production for ~60 days. Notes on what worked and what didn't.

The problem

Everything in one package. All trading bots + Telegram agent + master dashboard. Trade on perps, prediction markets, CEX, DEX, and meme coins -- all managed from your phone via Telegram.

What's in the box

All trading bots included
Telegram management agent
Master dashboard
Start/stop scripts
Full documentation
Setup guide

Code sample

# Basic structure
class Bot:
    def __init__(self, config):
        self.config = config

    def run(self):
        while True:
            self.scan()
            self.execute()

If you want the full working version with all the battle-tested edge cases
handled, I packaged it here: Complete Trading Bot Suite (All Bots + Agent + Dashboard)

Happy to answer questions about the architecture in the comments.

Portfolio value tracker with PnL calculation

Lucas Gragg — Fri, 01 May 2026 14:08:38 +0000

Packaged crypto price alert bot this week after running it in production for ~60 days. Notes on what worked and what didn't.

The problem

Never miss a price move again. Set custom alerts for any cryptocurrency across major exchanges and get instant notifications via Telegram, email, or Discord when your targets hit.

What's in the box

Real-time price monitoring across 10+ exchanges
Custom alert conditions (above, below, percent change)
Telegram, Discord, and email notifications
Portfolio watchlist with live price tracking
Historical alert log and price snapshots

Code sample

# Basic structure
class Bot:
    def __init__(self, config):
        self.config = config

    def run(self):
        while True:
            self.scan()
            self.execute()

If you want the full working version with all the battle-tested edge cases
handled, I packaged it here: Crypto Price Alert Bot

Happy to answer questions about the architecture in the comments.

Batch article generation at $0.00/post

Lucas Gragg — Thu, 30 Apr 2026 14:08:29 +0000

Packaged ai content writer this week after running it in production for ~60 days. Notes on what worked and what didn't.

The problem

Generate high-quality blog posts, product descriptions, social media captions, and marketing copy powered by LLM APIs. Includes templates for 20+ content types with tone and style customization.

What's in the box

20+ content templates (blogs, ads, emails, social)
Multiple LLM backend support (OpenAI, Groq, Anthropic)
Tone and style customization per template
Bulk content generation with CSV input
SEO keyword integration and readability scoring

Code sample

# Basic structure
class Bot:
    def __init__(self, config):
        self.config = config

    def run(self):
        while True:
            self.scan()
            self.execute()

If you want the full working version with all the battle-tested edge cases
handled, I packaged it here: AI Content Writer

Happy to answer questions about the architecture in the comments.

Solana vs Ethereum trading bot architecture

Lucas Gragg — Wed, 29 Apr 2026 14:08:19 +0000

Packaged multi-chain dex trading bot (8 chains) this week after running it in production for ~60 days. Notes on what worked and what didn't.

The problem

Trade on 8 blockchain networks from one bot. Supports Ethereum (Uniswap), Solana (Jupiter), BSC (PancakeSwap), Polygon (QuickSwap), Arbitrum (SushiSwap), Optimism (Velodrome), Avalanche (TraderJoe), and Cronos (VVS).

What's in the box

8 blockchain networks
8 DEX integrations
Token sniping and trading
Gas optimization
Multi-wallet support
Web dashboard

Code sample

# Basic structure
class Bot:
    def __init__(self, config):
        self.config = config

    def run(self):
        while True:
            self.scan()
            self.execute()

If you want the full working version with all the battle-tested edge cases
handled, I packaged it here: Multi-Chain DEX Trading Bot (8 Chains)

Happy to answer questions about the architecture in the comments.

5 crypto trading strategies every bot needs (with code)

Lucas Gragg — Tue, 28 Apr 2026 14:08:11 +0000

Packaged crypto exchange trading bot (python) this week after running it in production for ~60 days. Notes on what worked and what didn't.

The problem

Production-ready Python trading bot for any crypto exchange. Supports Binance, Bybit, Crypto.com, Coinbase via ccxt. Includes 5 strategies (Scalp, Swing, Grid, DCA, Sniper), real-time dashboard, stop-loss/take-profit, and Telegram alerts. Plug in your API keys and start trading.

What's in the box

5 trading strategies included
Real-time web dashboard
Telegram notifications
Multi-exchange support via ccxt
Risk management (SL/TP/trailing)
Position sizing and portfolio tracking

Code sample

# Basic structure
class Bot:
    def __init__(self, config):
        self.config = config

    def run(self):
        while True:
            self.scan()
            self.execute()

If you want the full working version with all the battle-tested edge cases
handled, I packaged it here: Crypto Exchange Trading Bot (Python)

Happy to answer questions about the architecture in the comments.

Arbitrage between prediction markets with Python

Lucas Gragg — Mon, 27 Apr 2026 14:08:03 +0000

Packaged kalshi/polymarket prediction market bot this week after running it in production for ~60 days. Notes on what worked and what didn't.

The problem

Automated prediction market trading bot. Scans Kalshi and Polymarket for mispriced events, calculates edge, and executes trades automatically. Includes position tracking, P&L dashboard, and Telegram alerts.

What's in the box

Kalshi API integration
Polymarket support
Edge detection algorithm
Auto-entry with configurable filters
Position management and exit logic
Web dashboard with live P&L

Code sample

# Basic structure
class Bot:
    def __init__(self, config):
        self.config = config

    def run(self):
        while True:
            self.scan()
            self.execute()

If you want the full working version with all the battle-tested edge cases
handled, I packaged it here: Kalshi/Polymarket Prediction Market Bot

Happy to answer questions about the architecture in the comments.

Reddit sentiment analysis with Groq

Lucas Gragg — Sun, 26 Apr 2026 14:07:54 +0000

Packaged reddit monitor bot this week after running it in production for ~60 days. Notes on what worked and what didn't.

The problem

Monitor any subreddit or keyword in real time and get instant alerts when relevant posts or comments appear. Ideal for brand monitoring, lead generation, competitor tracking, and trend discovery.

What's in the box

Real-time subreddit and keyword monitoring
Configurable alert filters (score, flair, author)
Telegram and Discord notification support
Sentiment analysis on matched posts
Export matched posts to CSV or database

Code sample

# Basic structure
class Bot:
    def __init__(self, config):
        self.config = config

    def run(self):
        while True:
            self.scan()
            self.execute()

If you want the full working version with all the battle-tested edge cases
handled, I packaged it here: Reddit Monitor Bot

Happy to answer questions about the architecture in the comments.

Lessons from 6 months of autonomous trading

Lucas Gragg — Sat, 25 Apr 2026 14:07:48 +0000

Packaged complete trading bot suite (all bots + agent + dashboard) this week after running it in production for ~60 days. Notes on what worked and what didn't.

The problem

Everything in one package. All trading bots + Telegram agent + master dashboard. Trade on perps, prediction markets, CEX, DEX, and meme coins -- all managed from your phone via Telegram.

What's in the box

All trading bots included
Telegram management agent
Master dashboard
Start/stop scripts
Full documentation
Setup guide

Code sample

# Basic structure
class Bot:
    def __init__(self, config):
        self.config = config

    def run(self):
        while True:
            self.scan()
            self.execute()

If you want the full working version with all the battle-tested edge cases
handled, I packaged it here: Complete Trading Bot Suite (All Bots + Agent + Dashboard)

Happy to answer questions about the architecture in the comments.

Twitter/X API v2 posting tutorial (2026)

Lucas Gragg — Fri, 24 Apr 2026 14:07:41 +0000

Packaged social media scheduler this week after running it in production for ~60 days. Notes on what worked and what didn't.

The problem

Schedule and auto-publish posts across Twitter, Reddit, and other platforms from a single dashboard. Grow your audience on autopilot with queue management, optimal timing, and content recycling.

What's in the box

Multi-platform posting (Twitter, Reddit, LinkedIn)
Visual content calendar and queue management
Optimal posting time suggestions based on engagement
Content recycling and evergreen post rotation
Analytics dashboard with engagement tracking

Code sample

# Basic structure
class Bot:
    def __init__(self, config):
        self.config = config

    def run(self):
        while True:
            self.scan()
            self.execute()

If you want the full working version with all the battle-tested edge cases
handled, I packaged it here: Social Media Scheduler

Happy to answer questions about the architecture in the comments.

Leverage trading math: position sizing for 5x perps

Lucas Gragg — Thu, 23 Apr 2026 14:07:33 +0000

Packaged hyperliquid perpetual futures trading bot this week after running it in production for ~60 days. Notes on what worked and what didn't.

The problem

Leveraged perp futures trading bot for Hyperliquid DEX. Supports long and short positions, up to 50x leverage, with built-in risk management. Includes momentum, mean-reversion, and breakout strategies.

What's in the box

Hyperliquid DEX integration
Long & short trading
Configurable leverage (1-50x)
3 built-in strategies
Trailing stop-loss
Web dashboard

Code sample

# Basic structure
class Bot:
    def __init__(self, config):
        self.config = config

    def run(self):
        while True:
            self.scan()
            self.execute()

If you want the full working version with all the battle-tested edge cases
handled, I packaged it here: Hyperliquid Perpetual Futures Trading Bot

Happy to answer questions about the architecture in the comments.