Prompt Engineering on SoloSoft

Agency Agents: 120+ AI Specialist Personas Transforming How We Work with AI

Fri, 01 May 2026 00:00:00 +0000

In the rapidly evolving landscape of AI-assisted development, a remarkable open-source project has captured the imagination of developers worldwide. Agency Agents, created by Marek Sitarzewski, brings together over 120 specialized AI agent personas organized into 12 divisions, effectively placing a complete AI agency at your fingertips.

What is Agency Agents?

Agency Agents is a carefully curated collection of specialized AI agent definitions, each with a unique personality, core mission, workflow process, concrete deliverables, and measurable success metrics. What makes this project truly revolutionary is what it does not contain: zero actual code. Every single agent is defined entirely in Markdown.

Awesome GPT Image 2: The Ultimate Open-Source Prompt Library for OpenAI's Image Generation

Fri, 01 May 2026 00:00:00 +0000

OpenAI’s GPT Image 2, launched in April 2026, represents a paradigm shift in AI image generation. Moving away from pure diffusion models toward an autoregressive, reasoning-driven architecture built on GPT-4o’s unified representation space, the model delivers near-perfect text rendering, cross-image character consistency, and native 2K resolution output. But with great power comes great complexity – crafting prompts that reliably exploit these capabilities is a craft that few have mastered.

Enter Awesome GPT Image 2 (github.com/YouMind-OpenLab/awesome-gpt-image-2), a community-driven, open-source prompt library that collects over 300 curated GPT Image 2 prompt cases, organizes them into reusable templates, and introduces a “Prompt as Code” methodology. Whether you are a creative agency producing branded content at scale, an e-commerce team generating product visuals, or a game studio developing character sheets, this library provides a structured, battle-tested foundation for reproducible, production-grade image generation.

LangGPT: Structured Prompt Engineering Framework

Fri, 01 May 2026 00:00:00 +0000

Prompt engineering has evolved from an art into a discipline, but most practitioners still write prompts as unstructured natural language, relying on intuition rather than methodology. LangGPT (langgptai/LangGPT on GitHub) brings structure, repeatability, and engineering rigor to prompt design by providing a comprehensive framework for creating, managing, and evaluating LLM prompts.

Developed by the LangGPT AI team, this open-source project has gained significant traction among AI practitioners who recognize that high-quality prompts require the same systematic approach as high-quality code. LangGPT introduces a template-based system where prompts are composed of reusable sections – role definitions, task descriptions, output constraints, examples, and reasoning instructions – assembled using variables and hierarchical composition.

Prompt Poet: Character.AI's Open-Source Prompt Engineering Framework

Fri, 01 May 2026 00:00:00 +0000

Prompt engineering has evolved from a niche skill into a critical discipline in AI application development. The difference between a good prompt and a great one can determine whether an LLM application delivers accurate, reliable results or produces inconsistent, error-prone output. Prompt Poet by Character.AI brings engineering rigor to this process, providing a structured framework for designing, testing, and optimizing prompts at scale.

Character.AI operates one of the world’s largest consumer AI platforms, serving millions of users daily across thousands of distinct AI characters. Managing prompts at this scale – where each character has unique personality traits, knowledge boundaries, and interaction patterns – requires tooling far beyond what simple text files or ad-hoc experimentation can provide. Prompt Poet grew out of this real-world need for systematic prompt management.

System Prompts Leaks: The Viral Open-Source Collection of AI System Instructions

Fri, 01 May 2026 00:00:00 +0000

The system prompt – the hidden set of instructions that defines an AI chatbot’s behavior, personality, and constraints – has become one of the most guarded secrets in the AI industry. Companies invest heavily in crafting these prompts to shape model behavior, enforce safety guidelines, and create distinctive product experiences. System Prompts Leaks pulls back the curtain on these hidden instructions, offering an open-source collection of extracted system prompts from virtually every major AI chatbot.

The repository has gone viral within the AI community, accumulating thousands of stars and attracting contributors who use various extraction techniques to reveal the system prompts of ChatGPT, Claude, Gemini, Grok, DeepSeek, Copilot, Perplexity, and dozens of other AI assistants. Each entry provides the raw system prompt text, the model it was extracted from, the extraction date, and notes on accuracy confidence.

CRAFT Framework Guide for Structured AI Workflows

Tue, 31 Mar 2026 00:00:00 +0000

Most teams still use AI in a fragile way. Someone opens ChatGPT, Claude, or a coding assistant, pastes a task, gets a decent answer, and then starts over the next day because the context is gone. That works for one-off prompts, but it breaks down when a project stretches across weeks, when multiple people need to reuse the same AI workflow, or when the output has to follow a repeatable standard. CRAFT Framework exists to address that gap. Rather than introducing a new model, it introduces structure around model usage: project variables, recipes, comments, personas, and handoff files that preserve continuity between sessions. Based on the public GitHub repository, official documentation, and related explanatory materials, CRAFT is best understood as a framework for turning AI conversations into durable operating systems for ongoing work. That makes it relevant not just to developers, but also to content teams, operators, and consultants who rely on AI repeatedly and need more than a clever prompt. In 2026, as AI tools increasingly become part of daily production workflows, CRAFT is interesting because it focuses on the layer many teams still lack: process discipline.