In this page
Automate documentation processes, empower your writers, and prove your value to the organisation
Is your documentation AI Agent friendly?
Training
What actually works (and what doesn’t)
Technical Writing
Over 30 AI agents and apps for managing documentation projects
Consultancy in using AI
AI usage statement
How to contact us
The two AI problems most organisations haven’t solved yet
1: AI tools without a strategy
Without a clear approach to quality, governance, and workflow, you’re likely generating more content, rather than better content.
And when AI draws on poorly managed source material, or operates without human checkpoints, you can end up with something confident but wrong. This is often harder to spot, and harder to fix, than no answer at all.
2: Your documentation isn’t ready to be an AI source
Poorly structured or outdated documentation already frustrates human readers. Feed it into an AI support bot, internal assistant, or automated workflow, and the problems just get worse. AI systems hallucinate, misdirect, and quietly erode trust in the tools you’ve invested in. This is especially true when no one is checking the output before it reaches a user.
The quality of what goes in determines the quality of what comes out. Unfortunately, many organisations discover this after they’ve deployed, not before.
Cherryleaf helps you use AI, good governance, and human-in-the-loop review to work more efficiently
Technical writers are usually judged on the finished documentation, but a lot of the time cost sits outside of the writing stage.
For example, in chasing down source information, and in reviewing AI-generated drafts against what’s actually true.
Based on the available research, a realistic planning range is an overall 10-30% reduction in time-to-publish across a team’s full workload, once you know where AI helps and where it needs control.
Automation and AI can still streamline your technical writing, but the gain comes from removing friction around source material and review, not just faster drafting (see how we worked out that range).
Technical documentation teams can waste time on repetitive, low-value tasks. The result is often outdated documents, writer burnout, and frustrated end-users. There’s pressure on you to produce more, be quicker, push costs down, and keep quality up.
AI can take on much of that repetitive load. But you need speed with accuracy.
Meanwhile, there’s pressure on you to produce more, be quicker, push costs down, and keep quality up.
Automation and AI can streamline and enhance your technical writing. They can help free writers to focus on the work that is the most rewarding and makes the most of their expertise. It can also help prove your value to the organisation, and deliver documentation that’s genuinely better for your users.
That’s why our consultancy approach considers three factors working together:
- Using AI well
- Good governance
- Clear standards and quality checks
- Human-in-the-loop review
The tools exist today, but many organisations lack the expertise, the governance model, and a clear implementation strategy to use them safely. Cherryleaf can help you build all three.
Good governance starts before the writing does
Governance means making sure your writers have good-quality source material to work from in the first place, as well as checking the output at the end. They need clear, accurate input from developers, and proper technical review from Subject Matter Experts (SMEs) before publication.
This is often where documentation projects lose the most time: chasing developers for information, waiting on SME reviews, and going back and forth to resolve ambiguities or contradictions.
AI can help reduce some of that friction. That doesn’t replace the developer’s input or the SME’s judgement, but it can make it faster and less painful for them to give it.
Using the right approach for you
There are different points in the technical writing process where you can use AI tools.
In addition, you could introduce workflow automations that operate behind the scenes, connecting different apps and services. For example, an automated documentation review and approval workflow, or a self-updating release notes generator.
There are also different ways you can use AI tools, such as:
- AI-powered coding assistants
- AI agents installed locally or through chatbots
- No code apps
- AI workflow solutions
We can help you identify the right ones for you.
Documentation automation services built by Technical Writers
Cherryleaf can help you seamlessly integrate the latest AI tools into your processes and standards and create AI agent-friendly content.
We offer:
- Training courses to give you the AI skills you need
- Technical writing services – creating documentation for AI apps
- Consultancy, including building a governance framework alongside your AI implementation
- Workshops
You’ll get independent advice from our experts in technical communication. Cherryleaf will listen to your needs, develop a bespoke strategy, and hold your hand. We’ll execute this plan together, if you want.
Let’s explore how AI can make your documentation more efficient, accurate, and valuable.
Is your documentation AI Agent friendly?
Recent research found that AI agents can silently truncate pages longer than their context window. For example, it could mean the last 15,000 characters of a 20,000-character page isn’t read. What’s good for humans sometimes isn’t not good for agents.
Is your documentation ready for AI retrieval?
If you’re deploying an AI support tool or internal assistant, your content quality determines your AI’s answer quality. Retrieval-Augmented Generation (RAG) is the technique that powers most AI assistants and support bots: the AI retrieves relevant content from your knowledge base, then generates an answer based on what it finds. If what it finds is outdated, contradictory, or too long to parse reliably, the answer will reflect that.
Cherryleaf’s RAG readiness audit tells you exactly what to fix, and in what order, before you go live.
Making your documentation findable by AI systems
AI agents, such as including coding assistants, AI search tools, and autonomous agents, increasingly read documentation directly. Standards like llms.txt help guide these agents to the most relevant content on your site. We help teams understand which AI-readiness improvements are worth making, and which are noise.
Not sure where your documentation is failing you?
Documentation debt accumulates silently: in outdated articles, missing coverage, inconsistent guidance, and content your AI tools can’t reliably use.
Cherryleaf’s Documentation Debt Audit identifies the highest-cost problems and tells you what to fix first.
You can schedule a discovery call
Most engagements begin with a free discovery call. From there, we can suggest a pathway that best matches your situation and needs. For example: an audit and roadmap, a training course or workshop, implementation, or a long-term optimisation arrangement.
A discovery call is a free, no-obligation, 45–60 minute conversation designed to determine whether there is a genuine fit between the your needs and our services.
AI training courses
Cherryleaf can give you the skills you need to use AI in technical writing.
Using AI in technical writing course
Our Using AI in technical writing course shows how to use generative AI to boost efficiency and create better deliverables. The course provides a framework that attendees can use to identify opportunities and best practices for integrating AI tools into your technical authoring processes – creating, managing, and delivering technical content.
Managing and mastering documentation projects with AI
Our Managing and mastering documentation projects with AI instructor-led course helps documentation project managers use AI strategically.
The course focuses on project and quality management. It looks at ways of using AI to accelerate documentation creation, improve quality, enable collaboration, and integrate AI directly into their content workflows and pipelines. It also covers how to build a custom AI agent stack for your organisation.
A strategic guide to AI for Technical Authors
Artificial Intelligence is changing technical writing. AI tools, particularly Large Language Models (LLMs), are changing how documentation is created, consumed, and maintained.
We wrote this free guide to help Technical Authors and Technical Writers understand and use AI tools effectively.
It explores three critical aspects of AI for the profession:
- Writing documentation optimised for LLM consumption
- Using AI to create new documentation outputs and formats
- Using AI to work more efficiently
See:
A collection of configurable technical writing skills.md files
Cherryleaf has developed a collection of eleven portable, company-neutral SKILL.md files for technical writers and documentation-focused AI assistants. The skills files should work for both Claude and Codex as Agent Skills, and can be customised to specific client environments.
AI apps for improving documentation – created by Technical Writers
Cherryleaf has developed over 30 apps that use AI to improve the quality and efficiency of documentation. We can show you how you can build these or similar apps, either as part of a project or consultancy, or as part of a training course for your company.
They include:
- Human and LLM content optimiser
- Reader simulator
- Diátaxis apps
- Automating changelogs and release notes
- Technical documentation dashboards
See: AI-driven documentation apps
Evidence retrieval and documentation readiness
Before a single word gets drafted, there’s a question worth answering: is this feature actually ready for documentation? We’ve built proof-of-concept tools that:
- Retrieve and rank evidence from Jira/Azure DevOps, GitHub, Confluence, and test systems into a single feature briefing pack, with the evidence trail intact
- Score documentation readiness (green/amber/red) against a defined standard, so gaps are visible before handover, not after
- Run an adaptive interview with developers or product owners that asks only the questions the evidence can’t already answer
This shifts writers’ time away from chasing missing information after the fact, and gives you data on which teams consistently hand over incomplete source material. See how this works.
Consultancy in using AI in technical communications
Integrating AI into your documentation workflow can seem daunting. Where do you start? Which tools are right for you? How do you keep quality and accountability intact as you scale up?
Cherryleaf can help you use AI to automate and improve your documentation processes, with governance and human review built in from the start. AI is not about replacing technical writers; it’s about empowering them. By integrating AI properly, you free your team from tedious, repetitive tasks, allowing them to focus on high-value activities like strategy, user advocacy, and creating exceptionally clear content.
We act as your strategic partner, helping you:
- Evaluate your current processes to identify the best opportunities for automation.
- Evaluate your current content to identify how AI could be used to improve it.
- Develop a tailored AI strategy that aligns with your business goals and includes clear governance and quality controls
- Implement the right tools and workflows for your team, with defined human checkpoints
- Train your writers to work effectively and alongside their new AI-powered assistants.
What actually works (and what doesn't)
Here are the key principles for success:
Targeted solutions for measurable outcomes
The first step is identifying the jobs for which AI is an excellent tool. Be realistic about tasks where other options may be better. AI is a powerful tool, not a universal remedy.
AI is very effective when you use it as a precision tool aimed at specific challenges. In other words, fixing bottlenecks in your documentation process. For example: a reduction in authoring time, a decrease in support tickets related to documentation, or a faster time-to-market for localised content.
By targeting these specific problems, you can implement AI solutions with clear, measurable outcomes.
Empowerment through bottom-up championing
In the past, technological developments have often been driven from the bottom up, rather than from the top down. Departments would quietly buy IT equipment and software that helped them do their jobs. The most successful projects succeed where there is momentum from the bottom as well as the top of the organisation. It’s the employees who will be using the tools daily.
Build the foundations for success
A company’s readiness is the single greatest predictor of success. Organisations that set clear metrics for what they want to achieve, establish strong governance for content quality, and invest in a high-quality, structured content infrastructure are far more likely to see a significant return on their AI investment.
Content quality is a prerequisite, not an outcome
Human review is what makes AI output trustworthy. AI tools amplify what’s already there.
If your documentation is scattered, inconsistent, or outdated, AI will produce outputs that are inconsistent and outdated, at a faster speed. Without a human checking that output before it reaches users, those errors reach them too.
The most important AI investment most teams can make is pairing better-quality source content with a proper human-in-the-loop review step. Everything else follows from that.
Often the real constraint is whether the writer was ever handed decent source material. If SMEs don’t give the technical writing team access to source information, test systems, and release decisions, AI has little more to work with than a human would. It can infer clues from code, tickets, or screenshots, but clues aren’t the same as clear source material. That’s why some of our most effective AI work happens before a writer starts drafting: retrieving evidence, checking whether a feature is actually ready for documenting, and asking only the questions that are still unanswered. Read more about fixing the source information bottleneck.
We also write developer and end user documentation for AI software
Cherryleaf has created user and developer documentation for a number of AI-related applications and APIs.
We combine deep technical understanding with clear communication to deliver:
- User guides that help your customers navigate AI features confidently, with real-world examples and step-by-step instructions
- Internal documentation that describes the functionality and configuration options
- Administrator documentation that streamlines deployment and management of AI systems
- Developer documentation that accelerates API integration and custom implementations
We translate intricate AI concepts to ensure every audience gets the information they need.
Our technical writing experts optimise content for AI chatbots by structuring guides so information can be easily ingested by large language models. This allows AI to reference materials and deliver concise, accurate answers to users.
AI usage statement
See Cherryleaf’s AI usage statement.
Contact us
Ready to talk strategy?
Book a discovery call. We’ll help you identify where AI can make a meaningful difference in your documentation process, and where it won’t.
Contact us today tell us your needs, and we’ll suggest the ideal AI solutions.
Want to start with a diagnostic?
Ask about a AI Readiness Audit or an AI Workflow Review. These are scoped engagements that give you a clear picture of where you are before committing to a full implementation.
Contact us today tell us your needs, and we’ll suggest the ideal AI solutions.