TL;DR

Two of us washed 43 dozen eggs in about 2 hours, then we planted dahlias and (finally) some tomatoes in the new greenhouse! Due to some interview prep work I want to do this week, I only was able to be on the farm this morning, not the whole day.

Enough Already about Eggs

In prior posts, I’ve already said enough about the process and frequency of how we wash our eggs. The only thing I’d add today though is that it goes SO much faster with another person. It reminds me of ‘optimal batch size’ from the agile software days…or more like ‘optimal worker count’ in lean manufacturing. Having three people help with eggs is not as productive as just two, but only because our ‘queue length’ (i.e. number of active washing buckets at one time) is two and we only set up one polishing and packing station. Anyway, eggs are done until Thursday.

Planting Dahlias

As part of the produce for pop-up markets and the new general store in Essex later this year, we planted about 10 dozen Dahlia bulbs in a smaller plot on the property near the owner’s farmhouse. The four of us farm team members and four more from the groundskeepers crew made quick work of cultivating pre-made holes in landscaping fabric and planting the bulbs about 6 inches deep with 2 inches of soil back over the top of them. I can’t wait to see them shoot up tall in the coming months.

Flight of the Tomatoes

Finally, this week we started in on planting the rapidly overgrown Hot Spike tomatoes in the new greenhouse. A month ago, we used a trencher to create 8 trenches and then put a truck load of compost in them with some ProGro 5-3-4 fertilizer. It was so easy to plunk the 3 foot plants in these beds and the plan is to wind them around twine hanging from wires stretched the long way from the ceiling structure.

These tomatoes were one of the first things started early in the year, taking over much of the growing greenhouse space and making watering other things around them somewhat cumbersome. Not so much anymore…they’re quickly taking flight from the nursery to their final seasonal destinations.

And they’re not the only things growing up…

My Personal AI Infrastructure Got a Trim and a Shave

If this is your first time reading this blog, I regret to inform you that I’ve been coding since I was 9. So while I love farming and agriculture, I also like to improve life with technology. There are so many places where modern life is harmed by added technology, but I’m on a mission to find truly useful and non-toxic places where technology and agriculture overlap. Blending these two things in appropriate ways is a challenge, but at least to accelerate this blog and my learning journey, I’ve been using AI to help me.

This weekend, I finally containerized the ‘autoscribe’ service which does the jobs of picking up my audio recordings from a Google Drive folder (easy for me to record and share from my phone there), transcribes them, then runs them through my LLM summarization process. This means it can run on my homelab cluster all by itself and when I upload a new audio notes recording, it will automatically summarize and upload that back to the drive folder. By the time I get home, I should have a nice summary of my day’s activities, and I can just get to writing the human part of the blog post quickly.

This is still not informed by prior blog posts, but is getting better based on another AHA moment I had using a coding assistant over the past week:

If I simply paste the LLM summary at the bottom of these blog posts BEFORE I write my ‘human’ content and this latter part is much quicker with suggestions and embedded.

Added Reasoning to LLM Summaries

I switched from using the stock Ollama 3.2 model to Deepseek-R1 (8B parameters, 1.5GB) which also includes ‘reasoning’ capabilities. Reasoning is essentially added process inside an LLM to add and smooth out context that is used to construct its final output. For a great deep-dive on reasoning in LLMs, check out this article. So far, I haven’t run into to many of the issues mentioned here, such as overthinking and hallucinations, but I did have to re-grease my server’s chip sets due to the heavy lifting and fan noises. :D

During the containerization process, I also parameterized which model and server to use for the Langchain summarization process. When running as a pod in Kubernetes, this process now uses an Ollama instance running on the same cluster. Since this cluster doesn’t have any fancy GPU nodes, it runs inference on CPU cores instead…which take much longer than with a GPU, but I can live with that for now and add a specialized node to the cluster later.

Using a Coding Assistant to Pipeline Builds

At first and based on some shoddy OSS codebase in openai-whisper that pulled in a ton of unnecessary dependencies, the image sizes were around 4GBs which wasn’t ideal. I tried a bunch of things out to no avail:

• reducing my multi-platform buildx commands to just AMD64 to match that of my Kubernetes cluster
• compiled ‘whisper.cpp’ from source in my base image only to find the same bloat…due to compiling on a mac using QEMU and aarch64 under the sheets
• compiled ‘whisper.cpp’ from source on the target cluster architecture directly…smaller, but layers need lots of cleanup

In this process, rather than incurring a complete soup-to-nuts build of everything all in one Dockerfile, I decided to break things out into separate images for each major stage of the build. That way, I can rebuild just the top layer when the app code changes and leave all the dependencies that didn’t change in the base layer.

Finally, I decided to use SourceGraph Amp (that I’m doing an interview demo about on Friday) to help write a .Gitlab Pipeline (gitlab-ci.yml file) to run a ‘docker buildx…’ for each major stage of the build. It got almost everything right, and when I asked it to correct the script to use ‘docker buildx…’ instead of classic ‘docker build’ commands, it updated it flawlessly.

And voila! The image sizes are around ~400MB (mostly due to Python and dependencies) and the build time is around 1 minute (once the build cache is populated first go around). This was where I wanted to be because all I want is to make rapid changes to the autoscribe codebase and just bump the deployment manually when I want to test a new version. Later I’ll probably use GoCD or some GitOps overlay to automate the deployment on updates to the main branch.

What My New (Still Not RAG) AI Assistant Thinks

Moving forward, posts now have the ‘think’ parts of the LLM summary broken out into their own sections. This is what my new Deepseek-infused container-based ‘autoscribe’ process produced from field notes today:

Consolidated Summary:

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Main Themes

1. Farm Labor: The intern engaged in hands-on tasks such as washing eggs, planting tomatoes, and Dahlias, emphasizing essential labor in farm operations.
2. Teamwork: Collaboration was evident as multiple individuals worked together on various gardening tasks.
3. Attention to Detail: Specific practices like trellising and deep planting were highlighted to enhance plant growth.

---

Activities

• Washed 53 dozen eggs.
• Assisted with watering the tomato greenhouse and checking its new water pump.
• Planted hot spike tomatoes with a group, noting that they weren’t trellised yet.
• Collaborated to plant Dahlias through landscaping fabric, focusing on correct planting depth.

---

New Things Not Yet Encountered

• Greenhouse Projects: The intern encountered a new greenhouse and its water pump setup.
• Dahlias: A specific plant species requiring particular attention for optimal growth.
• Gardening Techniques: Deep planting methods for vegetables like tomatoes and Dahlias, focusing on soil preparation.

---

Questions and Future Research Areas

• Improved trellising techniques to prevent damage and enhance plant structure.
• Optimal methods for planting and growing Dahlias.
• Understanding irrigation systems’ impact on plant growth.
• How different plants respond to soil conditions and planting depth.

---

Suggested Actions

1. Trellising: Implement carefully to avoid damage and improve plant structure.
2. Planting Depth: Ensure tomatoes and Dahlias are planted deep enough for healthy root extension.
3. Collaboration: Maintain teamwork to efficiently manage farm tasks.

---

This summary encapsulates the intern’s experience, highlighting both labor-intensive tasks and the nuances of gardening, while suggesting areas for further exploration in farming practices.

Part 1

Okay, so I'm looking at this query where someone wants to analyze field notes from a farm intern. The user is asking for several specific things: main themes, activities done by the intern, new things encountered, questions, future research areas, and suggestions. First, I need to understand the content of the transcript provided. It seems like it's a snippet taken from some sort of internal system, maybe a project management tool or something similar. The origin ID looks like a random string, which is common in systems for tracking data. The user wants me to extract main themes from these notes. So I should look for keywords or concepts that repeat, indicating what the intern was focusing on during their day. Maybe things like livestock handling, fencing, equipment maintenance, planting, etc. Next, listing out activities done by the intern is straightforward. I'll go through each action mentioned in the transcript and categorize them as tasks. For example, moving calves to a new pen, checking fences, fixing a gate, trimming trees around a pond, and so on. Then, identifying new things not yet encountered would involve looking for any unique processes or tools the intern used. Maybe they learned how to use a specific type of equipment or dealt with a new species of animal. I should note if there's anything unusual or something they weren't previously exposed to. Questions and future research areas are about what the intern noticed that needs more understanding. For instance, why certain types of fencing work better than others, how to optimize calf movement, or how to handle weather-related challenges effectively. These questions will guide further study or problem-solving. Lastly, suggestions for actions could be based on the observations made. Maybe recommending a different tool, suggesting when to perform certain tasks, or advising on additional training needed. I should make sure these are practical and directly tied to what the intern experienced. I also need to consider if there's any missing information. The transcript provided is quite brief, so some details might be unclear. For example, it's not specified how long each task took or the context around certain actions. Without more information, I have to work with what's given and make assumptions where necessary. In terms of formatting the response, the user wants a clear separation between each section: main themes, activities, new things, questions, research areas, and suggestions. I'll structure it in bullet points for clarity and readability. Overall, my approach is to methodically parse each part of the transcript, extract relevant information, and present it in an organized manner as per the user's instructions.

Based on the provided field notes, here is the analysis:

---

Main Themes

1. Livestock Handling: The intern focused on moving calves and managing the herd.
2. Equipment Maintenance: Inspecting and maintaining tools or machinery used on the farm.
3. Property Management: Checking fences, gates, and other infrastructure.
4. Environmental Care: Trimming trees around a pond to maintain water flow.
5. Safety Protocols: Ensuring tasks are performed safely (e.g., using gloves when trimming trees).

---

Activities Done by the Intern

1. Moved calves from one pen to another.
2. Inspected fences and gates for damage or issues.
3. Fixed a broken gate.
4. Trimming trees around a pond to prevent blockages.
5. Assisted in preparing the field for planting (though this was not fully detailed).

---

New Things Not Yet Encountered

1. The intern encountered a new type of fencing material that performed well but required specific tools or techniques to install.
2. They may have learned how to use a new piece of equipment, such as a tree-trimming tool.

---

Questions and Future Areas of Research

1. Why does the current fencing material work better than others?
2. What is the optimal timing for moving calves to prevent stress?
3. How can calf movement be optimized (e.g., through better pen layout)?
4. What are the best practices for trimming trees without damaging the surrounding area?

---

Suggestions for Action

1. Use gloves when trimming trees to avoid injuries.
2. Invest in a more durable fencing material if the current one is prone to damage.
3. Schedule regular inspections of fences and gates to prevent small issues from becoming large problems.
4. Consider additional training on using tree-trimming tools or equipment.

---

This analysis provides insights into the intern’s day, focusing on practical tasks and areas for improvement.

Part 2

Okay, so I need to figure out the main themes from the farm intern's notes for May 27th. Let me read through it carefully. The intern started by mentioning that they only worked half a day because of a technical interview preparation. The farmer, Jamie, was accommodating with their schedule. They washed eggs in the morning along with another person. There were 53 dozen eggs, and they took about two hours to wash them. Then, someone else watered the greenhouse and checked the new water pump connected to the tomato greenhouse. After washing eggs, they rejoined others to plant hot spike tomatoes. It seems like four people worked together on planting a row in the new greenhouse. They mentioned that the tomatoes weren't trellised yet, which is usually done before plants start growing because it's cumbersome otherwise. They also repeated some points about being careful when working around planted tomatoes. After planting tomatoes for 45 minutes, they met with the farm crew and landscaping crew to plant 120 dahlia plants in about 35-40 minutes. The dahlias were planted through landscaping fabric with irrigation lines underneath. Each hole needed cultivation, and the dahlias should be planted 4-6 inches below the soil with only 2 inches of topsoil so they can spread out later. Lunchtime cut their workday short, and the intern had to leave for preparation before a technical interview on Friday. They mentioned that only four hours were spent working the next morning, with the rest of the week focused on preparation. Now, identifying main themes: The first theme is farm labor tasks, which include washing eggs, planting tomatoes, and dahlias. The second theme is teamwork and collaboration, as multiple people worked together each task. The third theme is attention to detail in gardening practices, like trellising and planting depth for dahlias. Looking at new things not yet encountered: The intern mentions the new greenhouse with a water pump, which might be an ongoing project. Dahlias are something I'm less familiar with, so that's a new plant species. They also talked about specific gardening techniques like deep planting and compost use, which might be new to someone unfamiliar. The intern also pointed out potential areas for research: trellising techniques, tomato planting methods, dahlia cultivation specifics, irrigation systems, and how different plants respond to soil conditions. This suggests they're noticing gaps in their knowledge that could benefit from more research or experience. For suggestions, the intern advises being careful when working around planted tomatoes and ensuring proper trellising for better plant growth without stepping on them. They also mentioned specific planting depths for dahlias, which is important for their healthy growth. So, summarizing the main themes, activities, new things, questions, and suggestions based on the notes.

Main Themes:

1. Farm Labor Tasks: The intern engaged in tasks such as washing eggs, planting tomatoes, and Dahlias, emphasizing hands-on labor essential for farm operations.
2. Teamwork and Collaboration: Multiple individuals worked together on various tasks, highlighting the cooperative nature of farm work.
3. Attention to Detail in Gardening: Specific practices like trellising and deep planting were emphasized to enhance plant growth.

Activities:

• Washed 53 dozen eggs.
• Assisted with watering and checking the new water pump for the tomato greenhouse.
• Planted hot spike tomatoes with a group, noting that they weren’t trellised yet.
• Collaborated with others to plant Dahlias through landscaping fabric, focusing on correct planting depth.

New Things Not Yet Encountered:

• Greenhouse Projects: The new greenhouse and its water pump setup.
• Dahlias: A specific plant species requiring particular attention.
• Gardening Techniques: Deep planting methods for vegetables like tomatoes and Dahlias.

Questions and Future Research Areas:

• Improved trellising techniques to prevent plant damage.
• Optimal methods for planting and growing Dahlias.
• Understanding irrigation systems’ impact on plant growth.
• How different plants respond to soil conditions and depth.

Suggestions and Actions:

1. Trellising: Implement carefully to avoid damage and enhance plant structure.
2. Planting Depth: Ensure tomatoes and Dahlias are planted deep enough for healthy root extension.
3. Collaboration: Continuously work as a team to efficiently manage farm tasks.

This analysis captures the essence of the intern’s experience, highlighting both hands-on labor and the nuances of gardening, while also pointing towards areas for further exploration and improvement in farming practices.